{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\users\kamcd\Dropbox\CDK WORK\racial disparities essentialism\JOP replication files\Anoll Kam Marcellin Lucid Analyses.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}10 Jan 2025, 14:29:04
{txt}
{com}. 
. clear
{txt}
{com}. cd "C:/users/kamcd/Dropbox/CDK WORK/racial disparities essentialism/JOP replication files"
{res}C:\users\kamcd\Dropbox\CDK WORK\racial disparities essentialism\JOP replication files
{txt}
{com}. 
. *Saved csv file as an excel workbook
. *reading in the excel data
. use "Anoll Kam Marcellin Lucid March 2021 Survey.dta", clear
{txt}(Cleaned with no consent, <18, failed ACs, speeders, non-finishers dropped)

{com}. 
. *****Coding Covariates*****
. //age
. gen age01 = (age-18)/(93-18)
{txt}
{com}. lab var age01 "Age"
{txt}
{com}. 
. //educ
. gen ed6cat = (educ-1)/5
{txt}
{com}. lab def ed6cat 0"Less HS" 1">BA"
{txt}
{com}. lab val ed6cat ed6cat
{txt}
{com}. lab var ed6cat "Education"
{txt}
{com}. 
. //female
. recode gender (1=1 "female")(2=0)(else=.), gen(female)
{txt}(908 differences between {bf:gender} and {bf:female})

{com}. 
. //race
. gen race_all = .
{txt}(1,975 missing values generated)

{com}. replace race_all = 1 if race_1==1
{txt}(1,089 real changes made)

{com}. replace race_all = 2 if race_2==1
{txt}(435 real changes made)

{com}. replace race_all = 4 if race_4==1|race_6==1
{txt}(389 real changes made)

{com}. replace race_all = 3 if hisp_2==1|hisp_3==1|hisp_4==1|hisp_5==1
{txt}(367 real changes made)

{com}. lab def race_all 1"White" 2"Black" 3"Hispanic any race" 4"AAPI"
{txt}
{com}. lab val race_all race_all
{txt}
{com}. tab race_all

         {txt}race_all {c |}      Freq.     Percent        Cum.
{hline 18}{c +}{hline 35}
            White {c |}{res}        831       42.42       42.42
{txt}            Black {c |}{res}        384       19.60       62.02
{txt}Hispanic any race {c |}{res}        367       18.73       80.76
{txt}             AAPI {c |}{res}        377       19.24      100.00
{txt}{hline 18}{c +}{hline 35}
            Total {c |}{res}      1,959      100.00
{txt}
{com}. 
. recode race_all (1=1)(2/4=0)(else=.), gen(white)
{txt}(1,128 differences between {bf:race_all} and {bf:white})

{com}. recode race_all (2=1)(1 3 4=0)(else=.), gen(black)
{txt}(1,959 differences between {bf:race_all} and {bf:black})

{com}. recode race_all (3=1)(1 2 4=0)(else=.), gen(hispanic)
{txt}(1,959 differences between {bf:race_all} and {bf:hispanic})

{com}. recode race_all (4=1)(1 2 3=0)(else=.), gen(api)
{txt}(1,959 differences between {bf:race_all} and {bf:api})

{com}. lab var black "Black"
{txt}
{com}. lab var hispanic "Latino"
{txt}
{com}. lab var api "Asian"
{txt}
{com}. 
. //party 
. gen pid7cata = .
{txt}(1,975 missing values generated)

{com}. replace pid7cata = 0 if demf==1
{txt}(644 real changes made)

{com}. replace pid7cata = .17 if demf==2
{txt}(362 real changes made)

{com}. replace pid7cata = .33 if indf==2
{txt}(130 real changes made)

{com}. replace pid7cata = .5 if indf==3
{txt}(218 real changes made)

{com}. replace pid7cata = .67 if indf==1
{txt}(79 real changes made)

{com}. replace pid7cata = .83 if gopf==2
{txt}(223 real changes made)

{com}. replace pid7cata = 1 if gopf==1
{txt}(316 real changes made)

{com}. tab pid7cata

   {txt}pid7cata {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        644       32.66       32.66
{txt}        .17 {c |}{res}        362       18.36       51.01
{txt}        .33 {c |}{res}        130        6.59       57.61
{txt}         .5 {c |}{res}        218       11.05       68.66
{txt}        .67 {c |}{res}         79        4.01       72.67
{txt}        .83 {c |}{res}        223       11.31       83.98
{txt}          1 {c |}{res}        316       16.02      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,972      100.00
{txt}
{com}. lab var pid7cata "Party ID"
{txt}
{com}. 
. recode pid7cata (0/.4=1)(.5/1=0)(else=.), gen(dem)
{txt}(1,972 differences between {bf:pid7cata} and {bf:dem})

{com}. recode pid7cata (0/.51=0)(.6/1=1)(else=.), gen(rep)
{txt}(1,012 differences between {bf:pid7cata} and {bf:rep})

{com}. recode pid7cata (0/.34=0)(.5=.5)(.6/1=1)(else=.), gen(pid3cata)
{txt}(794 differences between {bf:pid7cata} and {bf:pid3cata})

{com}. recode pid7cata (0/.34=0 "Dem")(.5=.)(.6/1=1 "GOP")(else=.), gen(pid2cata)
{txt}(1,012 differences between {bf:pid7cata} and {bf:pid2cata})

{com}. lab var pid2cata "Dem (0) or GOP (1)"
{txt}
{com}. 
. //Five analytical groups
. gen fivegroups = .
{txt}(1,975 missing values generated)

{com}. replace fivegroups = 1 if api==1
{txt}(377 real changes made)

{com}. replace fivegroups = 2 if black==1
{txt}(384 real changes made)

{com}. replace fivegroups = 3 if hispanic==1
{txt}(367 real changes made)

{com}. replace fivegroups = 4 if white==1 & pid2cata==0
{txt}(410 real changes made)

{com}. replace fivegroups = 5 if white==1 & pid2cata==1
{txt}(406 real changes made)

{com}. lab def fivegroups 1"Asian" 2"Black" 3"Latino" 4"White DEM" 5"White GOP"
{txt}
{com}. lab val fivegroups fivegroups
{txt}
{com}. tab fivegroups

 {txt}fivegroups {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
      Asian {c |}{res}        377       19.39       19.39
{txt}      Black {c |}{res}        384       19.75       39.15
{txt}     Latino {c |}{res}        367       18.88       58.02
{txt}  White DEM {c |}{res}        410       21.09       79.12
{txt}  White GOP {c |}{res}        406       20.88      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,944      100.00
{txt}
{com}. 
. //*Question 3: what determines your own race battery
. recode moduleC_2_1 moduleC_2_2 moduleC_2_3 moduleC_2_4 moduleC_2_5 moduleC_2_6 moduleC_2_7 (1=1)(2=0)(3=0)(4=0), gen(myrace_DNA myrace_culture myrace_history myrace_choices myrace_forms myrace_toldme myrace_physical)
{txt}(880 differences between {bf:moduleC_2_1} and {bf:myrace_DNA})
(1,409 differences between {bf:moduleC_2_2} and {bf:myrace_culture})
(1,370 differences between {bf:moduleC_2_3} and {bf:myrace_history})
(1,503 differences between {bf:moduleC_2_4} and {bf:myrace_choices})
(1,471 differences between {bf:moduleC_2_5} and {bf:myrace_forms})
(1,827 differences between {bf:moduleC_2_6} and {bf:myrace_toldme})
(1,175 differences between {bf:moduleC_2_7} and {bf:myrace_physical})

{com}. lab def myrace 1"Strongly" 0"Not strongly", modify
{txt}
{com}. lab val myrace_DNA myrace_culture myrace_history myrace_choices myrace_forms myrace_toldme myrace_physical myrace  
{txt}
{com}. sum myrace_DNA myrace_culture myrace_history myrace_choices myrace_forms myrace_toldme myrace_physical

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}myrace_DNA {c |}{res}      1,975    .5544304    .4971544          0          1
{txt}myrace_cul~e {c |}{res}      1,975    .2865823    .4522792          0          1
{txt}myrace_his~y {c |}{res}      1,975    .3063291    .4610848          0          1
{txt}myrace_cho~s {c |}{res}      1,975    .2389873     .426573          0          1
{txt}myrace_forms {c |}{res}      1,975    .2551899    .4360783          0          1
{txt}{hline 13}{c +}{hline 57}
myrace_tol~e {c |}{res}      1,975    .0749367    .2633559          0          1
{txt}myrace_phy~l {c |}{res}      1,975    .4050633    .4910286          0          1
{txt}
{com}. 
. //recoding to capture folks who state strongly or somewhat
. //combining No and DK together
. recode moduleC_2_1 moduleC_2_2 moduleC_2_3 moduleC_2_4 moduleC_2_5 moduleC_2_6 moduleC_2_7 (1 2=1)(3 4=0), gen(myrace_DNA2 myrace_culture2 myrace_history2 myrace_choices2 myrace_forms2 myrace_toldme2 myrace_physical2)
{txt}(880 differences between {bf:moduleC_2_1} and {bf:myrace_DNA2})
(1,409 differences between {bf:moduleC_2_2} and {bf:myrace_culture2})
(1,370 differences between {bf:moduleC_2_3} and {bf:myrace_history2})
(1,503 differences between {bf:moduleC_2_4} and {bf:myrace_choices2})
(1,471 differences between {bf:moduleC_2_5} and {bf:myrace_forms2})
(1,827 differences between {bf:moduleC_2_6} and {bf:myrace_toldme2})
(1,175 differences between {bf:moduleC_2_7} and {bf:myrace_physical2})

{com}. lab def myrace2 1"Strongly or somewhat" 0"Not at all"
{txt}
{com}. lab val myrace_DNA2 myrace_culture2 myrace_history2 myrace_choices2 myrace_forms2 myrace_toldme2 myrace_physical2 myrace2
{txt}
{com}. 
. //% DK/ref
. tab1 moduleC_2_1- moduleC_2_7

{res}-> tabulation of moduleC_2_1  

  {txt}Information contained in my DNA {c |}      Freq.     Percent        Cum.
{hline 34}{c +}{hline 35}
      Strongly determines my race {c |}{res}      1,095       55.44       55.44
{txt}      Somewhat determines my race {c |}{res}        600       30.38       85.82
{txt}Does not at all determine my race {c |}{res}        179        9.06       94.89
{txt}              Don’t know/not sure {c |}{res}        101        5.11      100.00
{txt}{hline 34}{c +}{hline 35}
                            Total {c |}{res}      1,975      100.00

-> tabulation of moduleC_2_2  

{txt}Culture shared with other members {c |}
               of my racial group {c |}      Freq.     Percent        Cum.
{hline 34}{c +}{hline 35}
      Strongly determines my race {c |}{res}        566       28.66       28.66
{txt}      Somewhat determines my race {c |}{res}        804       40.71       69.37
{txt}Does not at all determine my race {c |}{res}        475       24.05       93.42
{txt}              Don’t know/not sure {c |}{res}        130        6.58      100.00
{txt}{hline 34}{c +}{hline 35}
                            Total {c |}{res}      1,975      100.00

-> tabulation of moduleC_2_3  

{txt}History shared with other members {c |}
               of my racial group {c |}      Freq.     Percent        Cum.
{hline 34}{c +}{hline 35}
      Strongly determines my race {c |}{res}        605       30.63       30.63
{txt}      Somewhat determines my race {c |}{res}        808       40.91       71.54
{txt}Does not at all determine my race {c |}{res}        428       21.67       93.22
{txt}              Don’t know/not sure {c |}{res}        134        6.78      100.00
{txt}{hline 34}{c +}{hline 35}
                            Total {c |}{res}      1,975      100.00

-> tabulation of moduleC_2_4  

 {txt}My own choices about my identity {c |}      Freq.     Percent        Cum.
{hline 34}{c +}{hline 35}
      Strongly determines my race {c |}{res}        472       23.90       23.90
{txt}      Somewhat determines my race {c |}{res}        552       27.95       51.85
{txt}Does not at all determine my race {c |}{res}        796       40.30       92.15
{txt}              Don’t know/not sure {c |}{res}        155        7.85      100.00
{txt}{hline 34}{c +}{hline 35}
                            Total {c |}{res}      1,975      100.00

-> tabulation of moduleC_2_5  

   {txt}What race I select on official {c |}
                            forms {c |}      Freq.     Percent        Cum.
{hline 34}{c +}{hline 35}
      Strongly determines my race {c |}{res}        504       25.52       25.52
{txt}      Somewhat determines my race {c |}{res}        560       28.35       53.87
{txt}Does not at all determine my race {c |}{res}        768       38.89       92.76
{txt}              Don’t know/not sure {c |}{res}        143        7.24      100.00
{txt}{hline 34}{c +}{hline 35}
                            Total {c |}{res}      1,975      100.00

-> tabulation of moduleC_2_6  

        {txt}What someone else told me {c |}      Freq.     Percent        Cum.
{hline 34}{c +}{hline 35}
      Strongly determines my race {c |}{res}        148        7.49        7.49
{txt}      Somewhat determines my race {c |}{res}        331       16.76       24.25
{txt}Does not at all determine my race {c |}{res}      1,305       66.08       90.33
{txt}              Don’t know/not sure {c |}{res}        191        9.67      100.00
{txt}{hline 34}{c +}{hline 35}
                            Total {c |}{res}      1,975      100.00

-> tabulation of moduleC_2_7  

  {txt}Physical traits like skin color {c |}      Freq.     Percent        Cum.
{hline 34}{c +}{hline 35}
      Strongly determines my race {c |}{res}        800       40.51       40.51
{txt}      Somewhat determines my race {c |}{res}        744       37.67       78.18
{txt}Does not at all determine my race {c |}{res}        350       17.72       95.90
{txt}              Don’t know/not sure {c |}{res}         81        4.10      100.00
{txt}{hline 34}{c +}{hline 35}
                            Total {c |}{res}      1,975      100.00
{txt}
{com}. egen ref_myrace = anycount(moduleC_2_1- moduleC_2_7), val(4)
{res}{txt}
{com}. tab ref_myrace

  {txt}see notes {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}      1,544       78.18       78.18
{txt}          1 {c |}{res}        249       12.61       90.78
{txt}          2 {c |}{res}         82        4.15       94.94
{txt}          3 {c |}{res}         27        1.37       96.30
{txt}          4 {c |}{res}         13        0.66       96.96
{txt}          5 {c |}{res}         12        0.61       97.57
{txt}          6 {c |}{res}          7        0.35       97.92
{txt}          7 {c |}{res}         41        2.08      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,975      100.00
{txt}
{com}. 
. forval v=1/7 {c -(}
{txt}  2{com}. recode moduleC_2_`v' (1 2=1)(3 4 =0)(else=.), gen(myraceagree`v')
{txt}  3{com}. {c )-}
{txt}(880 differences between {bf:moduleC_2_1} and {bf:myraceagree1})
(1,409 differences between {bf:moduleC_2_2} and {bf:myraceagree2})
(1,370 differences between {bf:moduleC_2_3} and {bf:myraceagree3})
(1,503 differences between {bf:moduleC_2_4} and {bf:myraceagree4})
(1,471 differences between {bf:moduleC_2_5} and {bf:myraceagree5})
(1,827 differences between {bf:moduleC_2_6} and {bf:myraceagree6})
(1,175 differences between {bf:moduleC_2_7} and {bf:myraceagree7})

{com}. 
. set scheme s1mono
{txt}
{com}. **********START FIGURE 1**********
. //Figure 1. Agree + Strongly Agree, by racial group
. forval v=1/7 {c -(}
{txt}  2{com}. recode moduleC_2_`v' (1=1)(2 3 4 =0)(else=.), gen(myraceSTRagree`v')
{txt}  3{com}. {c )-}
{txt}(880 differences between {bf:moduleC_2_1} and {bf:myraceSTRagree1})
(1,409 differences between {bf:moduleC_2_2} and {bf:myraceSTRagree2})
(1,370 differences between {bf:moduleC_2_3} and {bf:myraceSTRagree3})
(1,503 differences between {bf:moduleC_2_4} and {bf:myraceSTRagree4})
(1,471 differences between {bf:moduleC_2_5} and {bf:myraceSTRagree5})
(1,827 differences between {bf:moduleC_2_6} and {bf:myraceSTRagree6})
(1,175 differences between {bf:moduleC_2_7} and {bf:myraceSTRagree7})

{com}. 
. forval v=1/7 {c -(}
{txt}  2{com}. recode moduleC_2_`v' (2=1)(1 3 4 =0)(else=.), gen(myraceONLYagree`v')
{txt}  3{com}. {c )-}
{txt}(1,975 differences between {bf:moduleC_2_1} and {bf:myraceONLYagree1})
(1,975 differences between {bf:moduleC_2_2} and {bf:myraceONLYagree2})
(1,975 differences between {bf:moduleC_2_3} and {bf:myraceONLYagree3})
(1,975 differences between {bf:moduleC_2_4} and {bf:myraceONLYagree4})
(1,975 differences between {bf:moduleC_2_5} and {bf:myraceONLYagree5})
(1,975 differences between {bf:moduleC_2_6} and {bf:myraceONLYagree6})
(1,975 differences between {bf:moduleC_2_7} and {bf:myraceONLYagree7})

{com}. 
. //for text, % by fivegroups:
. tab myraceagree1 fivegroups, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

 RECODE of {c |}
moduleC_2_ {c |}
         1 {c |}
(Informati {c |}
        on {c |}
 contained {c |}                       fivegroups
in my DNA) {c |}     Asian      Black     Latino  White DEM  White GOP {c |}     Total
{hline 11}{c +}{hline 55}{c +}{hline 10}
         0 {c |}{res}        45         54         67         43         63 {txt}{c |}{res}       272 
           {txt}{c |}{res}     11.94      14.06      18.26      10.49      15.52 {txt}{c |}{res}     13.99 
{txt}{hline 11}{c +}{hline 55}{c +}{hline 10}
         1 {c |}{res}       332        330        300        367        343 {txt}{c |}{res}     1,672 
           {txt}{c |}{res}     88.06      85.94      81.74      89.51      84.48 {txt}{c |}{res}     86.01 
{txt}{hline 11}{c +}{hline 55}{c +}{hline 10}
     Total {c |}{res}       377        384        367        410        406 {txt}{c |}{res}     1,944 
           {txt}{c |}{res}    100.00     100.00     100.00     100.00     100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. tab myraceSTRagree1 fivegroups, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

 RECODE of {c |}
moduleC_2_ {c |}
         1 {c |}
(Informati {c |}
        on {c |}
 contained {c |}                       fivegroups
in my DNA) {c |}     Asian      Black     Latino  White DEM  White GOP {c |}     Total
{hline 11}{c +}{hline 55}{c +}{hline 10}
         0 {c |}{res}       186        144        183        181        167 {txt}{c |}{res}       861 
           {txt}{c |}{res}     49.34      37.50      49.86      44.15      41.13 {txt}{c |}{res}     44.29 
{txt}{hline 11}{c +}{hline 55}{c +}{hline 10}
         1 {c |}{res}       191        240        184        229        239 {txt}{c |}{res}     1,083 
           {txt}{c |}{res}     50.66      62.50      50.14      55.85      58.87 {txt}{c |}{res}     55.71 
{txt}{hline 11}{c +}{hline 55}{c +}{hline 10}
     Total {c |}{res}       377        384        367        410        406 {txt}{c |}{res}     1,944 
           {txt}{c |}{res}    100.00     100.00     100.00     100.00     100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. 
. //% STRONGLY AGREE BY FIVEGROUPS
. forval v=1/5 {c -(}
{txt}  2{com}. preserve
{txt}  3{com}. collapse myraceSTRagree1-myraceSTRagree7 if fivegroups==`v'
{txt}  4{com}. gen id = _n
{txt}  5{com}. reshape long myraceSTRagree, i(id) j(Q)
{txt}  6{com}. lab def Q 1 "DNA" 2 "Culture" 3 "History" 4 "My Choices" 5 "Select on Forms" 6 "What Someone Told Me" 7"Physical Traits"
{txt}  7{com}. lab val Q Q
{txt}  8{com}. gen myraceSTRagreepercent_`v' = myraceSTRagree*100
{txt}  9{com}. save myraceSTRagreepercent_`v', replace
{txt} 10{com}. restore
{txt} 11{com}. {c )-}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceSTRagree1 myraceSTRagree2 ... myraceSTRagree7{txt}->{res}myraceSTRagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceSTRagreepercent_1.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceSTRagreepercent_1.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceSTRagree1 myraceSTRagree2 ... myraceSTRagree7{txt}->{res}myraceSTRagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceSTRagreepercent_2.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceSTRagreepercent_2.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceSTRagree1 myraceSTRagree2 ... myraceSTRagree7{txt}->{res}myraceSTRagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceSTRagreepercent_3.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceSTRagreepercent_3.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceSTRagree1 myraceSTRagree2 ... myraceSTRagree7{txt}->{res}myraceSTRagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceSTRagreepercent_4.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceSTRagreepercent_4.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceSTRagree1 myraceSTRagree2 ... myraceSTRagree7{txt}->{res}myraceSTRagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceSTRagreepercent_5.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceSTRagreepercent_5.dta{rm}
saved
{p_end}

{com}. 
. //% AGREE BY FIVEGROUPS
. forval v=1/5 {c -(}
{txt}  2{com}. preserve
{txt}  3{com}. collapse myraceONLYagree1-myraceONLYagree7 if fivegroups==`v'
{txt}  4{com}. gen id = _n
{txt}  5{com}. reshape long myraceONLYagree, i(id) j(Q)
{txt}  6{com}. lab def Q 1 "DNA" 2 "Culture" 3 "History" 4 "My Choices" 5 "Select on Forms" 6 "What Someone Told Me" 7"Physical Traits"
{txt}  7{com}. lab val Q Q
{txt}  8{com}. gen myraceONLYagreepercent_`v' = myraceONLYagree*100
{txt}  9{com}. save myraceONLYagreepercent_`v', replace
{txt} 10{com}. restore
{txt} 11{com}. {c )-}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceONLYagree1 myraceONLYagree2 ... myraceONLYagree7{txt}->{res}myraceONLYagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceONLYagreepercent_1.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceONLYagreepercent_1.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceONLYagree1 myraceONLYagree2 ... myraceONLYagree7{txt}->{res}myraceONLYagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceONLYagreepercent_2.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceONLYagreepercent_2.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceONLYagree1 myraceONLYagree2 ... myraceONLYagree7{txt}->{res}myraceONLYagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceONLYagreepercent_3.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceONLYagreepercent_3.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceONLYagree1 myraceONLYagree2 ... myraceONLYagree7{txt}->{res}myraceONLYagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceONLYagreepercent_4.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceONLYagreepercent_4.dta{rm}
saved
{p_end}
{res}{txt}(j = 1 2 3 4 5 6 7)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           1   {txt}->   {res}7           
{txt}Number of variables        {res}           8   {txt}->   {res}3           
{txt}j variable (7 values)                     ->   {res}Q
{txt}xij variables:
{res}myraceONLYagree1 myraceONLYagree2 ... myraceONLYagree7{txt}->{res}myraceONLYagree
{txt}{hline 77}
{p 0 4 2}
(file {bf}
myraceONLYagreepercent_5.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
myraceONLYagreepercent_5.dta{rm}
saved
{p_end}

{com}. 
. //PLOTTING %STR AGREE + AGREE BY FIVEGROUPS
. forval v=1/5 {c -(}
{txt}  2{com}. preserve
{txt}  3{com}. clear
{txt}  4{com}. use myraceSTRagreepercent_`v', clear
{txt}  5{com}.         gen str10 group`v' = "Asian" if `v'==1
{txt}  6{com}.         replace group`v' = "Black" if `v'==2
{txt}  7{com}.         replace group`v' = "Latino" if `v'==3
{txt}  8{com}.         replace group`v' = "White DEM" if `v'==4
{txt}  9{com}.         replace group`v' = "White GOP" if `v'==5
{txt} 10{com}.         local h = group`v'
{txt} 11{com}. merge 1:1 Q using myraceONLYagreepercent_`v'
{txt} 12{com}. recode Q (1=1 "DNA")(7=2 "Phys Traits")(3=3 "History")(2=4 "Culture") (5=5 "Forms")(4=6 "Choices")(6=7 "Told Me"), gen(graphorder)
{txt} 13{com}. graph hbar myraceSTRagreepercent myraceONLYagreepercent, over(graphorder) ///
> name(myraceboth_`v', replace) ///
> title("`h' Respondents", size(medium)) ytitle(" ") xsize(5) ysize(4) graphregion(margin(l+10)) stack asyvars legend(lab(1 "% Strongly") lab(2 "% Somewhat") symxsize(5) keygap(.5) forcesize)
{txt} 14{com}. restore
{txt} 15{com}. {c )-}
{txt}(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
{res}{txt}(label {bf:{txt}Q} already defined)

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}               7{txt}  (_merge==3)
{col 5}{hline 41}
(4 differences between {bf:Q} and {bf:graphorder})
{res}{txt}(7 missing values generated)
(7 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
{res}{txt}(label {bf:{txt}Q} already defined)

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}               7{txt}  (_merge==3)
{col 5}{hline 41}
(4 differences between {bf:Q} and {bf:graphorder})
{res}{txt}(7 missing values generated)
(0 real changes made)
(7 real changes made)
(0 real changes made)
(0 real changes made)
{res}{txt}(label {bf:{txt}Q} already defined)

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}               7{txt}  (_merge==3)
{col 5}{hline 41}
(4 differences between {bf:Q} and {bf:graphorder})
{res}{txt}(7 missing values generated)
(0 real changes made)
(0 real changes made)
(7 real changes made)
(0 real changes made)
{res}{txt}(label {bf:{txt}Q} already defined)

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}               7{txt}  (_merge==3)
{col 5}{hline 41}
(4 differences between {bf:Q} and {bf:graphorder})
{res}{txt}(7 missing values generated)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(7 real changes made)
{res}{txt}(label {bf:{txt}Q} already defined)

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}               7{txt}  (_merge==3)
{col 5}{hline 41}
(4 differences between {bf:Q} and {bf:graphorder})
{res}{txt}
{com}. 
. graph combine myraceboth_1 myraceboth_2 myraceboth_3 myraceboth_4 myraceboth_5, row(2) title("To what extent do the following factors determine your race?", size(medium)) xsize(6.5) ysize(4.5) imargin(medium) iscale(.55) ycommon xcommon
{res}{txt}
{com}. graph export Figure1.pdf, replace
{txt}{p 0 4 2}
file {bf}
Figure1.pdf{rm}
saved as
PDF
format
{p_end}

{com}. **********END FIGURE 1**********
. 
. *****cleaning up directory*****
. forval v=1/5 {c -(}
{txt}  2{com}. erase myraceSTRagreepercent_`v'.dta
{txt}  3{com}. erase myraceONLYagreepercent_`v'.dta
{txt}  4{com}. {c )-}
{txt}
{com}. 
. *****FN 11: PAIRWISE COMPARISONS*****
. //Difference of proportions test
. //create comparison groups
. gen AB = .
{txt}(1,975 missing values generated)

{com}. replace AB=1 if fivegroups==1|fivegroups==2
{txt}(761 real changes made)

{com}. gen AL = .
{txt}(1,975 missing values generated)

{com}. replace AL=1 if fivegroups==1|fivegroups==3
{txt}(744 real changes made)

{com}. gen AWD = .
{txt}(1,975 missing values generated)

{com}. replace AWD=1 if fivegroups==1|fivegroups==4
{txt}(787 real changes made)

{com}. gen AWR = .
{txt}(1,975 missing values generated)

{com}. replace AWR=1 if fivegroups==1|fivegroups==5
{txt}(783 real changes made)

{com}. gen BL = .
{txt}(1,975 missing values generated)

{com}. replace BL=1 if fivegroups==2|fivegroups==3
{txt}(751 real changes made)

{com}. gen BWD = .
{txt}(1,975 missing values generated)

{com}. replace BWD=1 if fivegroups==2|fivegroups==4
{txt}(794 real changes made)

{com}. gen BWR = .
{txt}(1,975 missing values generated)

{com}. replace BWR=1 if fivegroups==2|fivegroups==5
{txt}(790 real changes made)

{com}. gen LWD = .
{txt}(1,975 missing values generated)

{com}. replace LWD=1 if fivegroups==3|fivegroups==4
{txt}(777 real changes made)

{com}. gen LWR = .
{txt}(1,975 missing values generated)

{com}. replace LWR=1 if fivegroups==3|fivegroups==5
{txt}(773 real changes made)

{com}. gen WDR = .
{txt}(1,975 missing values generated)

{com}. replace WDR=1 if fivegroups==4|fivegroups==5
{txt}(816 real changes made)

{com}. 
. *****Strongly or Somewhat: DNA*****
. *****Multiple Factors*****
. egen howmanyagree = anycount(myrace_DNA2 myrace_culture2 myrace_history2 myrace_choices2 myrace_physical2 myrace_forms2 myrace_toldme2 ), val(1)
{res}{txt}
{com}. recode howmanyagree (0 1=0)(2/7=1 "Selected Agree with More than One Item"), gen(morethanone)
{txt}(1,913 differences between {bf:howmanyagree} and {bf:morethanone})

{com}. 
. *****"Opposing" Factors: DNA plus any constructivist (culture, history, choices, forms, told me)*****
. egen anyconstructivist = anymatch(myrace_culture2 myrace_history2 myrace_choices2 myrace_forms2 myrace_toldme2), val(1)
{res}{txt}
{com}. gen DNAanycon= anyconstructivist +myrace_DNA2
{txt}
{com}. replace DNAanycon = 0 if DNAanycon==1
{txt}(368 real changes made)

{com}. replace DNAanycon =1 if DNAanycon==2
{txt}(1,527 real changes made)

{com}. 
. lab var morethanone "Proportion Agreeing with >1 Factor"
{txt}
{com}. lab var DNAanycon "Proportion Agreeing with DNA + Any Constructivist Factor"
{txt}
{com}. lab var myrace_DNA2 "Proportion Agreeing with DNA"
{txt}
{com}. lab var myrace_DNA "Proportion Strongly Agreeing with DNA"
{txt}
{com}. lab var fivegroups "Subgroups"
{txt}
{com}. 
. *****In text*****
. tab fivegroups morethanone, row
{txt}
{c TLC}{hline 16}{c TRC}
{c |} Key{col 18}{c |}
{c LT}{hline 16}{c RT}
{c |}{space 3}{it:frequency}{col 18}{c |}
{c |}{space 1}{it:row percentage}{col 18}{c |}
{c BLC}{hline 16}{c BRC}

           {c |}  Proportion Agreeing
           {c |}    with >1 Factor
 Subgroups {c |}         0  Selected  {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
     Asian {c |}{res}        13        364 {txt}{c |}{res}       377 
           {txt}{c |}{res}      3.45      96.55 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Black {c |}{res}        22        362 {txt}{c |}{res}       384 
           {txt}{c |}{res}      5.73      94.27 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
    Latino {c |}{res}        33        334 {txt}{c |}{res}       367 
           {txt}{c |}{res}      8.99      91.01 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
 White DEM {c |}{res}        29        381 {txt}{c |}{res}       410 
           {txt}{c |}{res}      7.07      92.93 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
 White GOP {c |}{res}        48        358 {txt}{c |}{res}       406 
           {txt}{c |}{res}     11.82      88.18 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       145      1,799 {txt}{c |}{res}     1,944 
           {txt}{c |}{res}      7.46      92.54 {txt}{c |}{res}    100.00 
{txt}
{com}. tab fivegroups DNAanycon, row
{txt}
{c TLC}{hline 16}{c TRC}
{c |} Key{col 18}{c |}
{c LT}{hline 16}{c RT}
{c |}{space 3}{it:frequency}{col 18}{c |}
{c |}{space 1}{it:row percentage}{col 18}{c |}
{c BLC}{hline 16}{c BRC}

           {c |}  Proportion Agreeing
           {c |}    with DNA + Any
           {c |} Constructivist Factor
 Subgroups {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
     Asian {c |}{res}        67        310 {txt}{c |}{res}       377 
           {txt}{c |}{res}     17.77      82.23 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Black {c |}{res}        81        303 {txt}{c |}{res}       384 
           {txt}{c |}{res}     21.09      78.91 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
    Latino {c |}{res}        89        278 {txt}{c |}{res}       367 
           {txt}{c |}{res}     24.25      75.75 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
 White DEM {c |}{res}        73        337 {txt}{c |}{res}       410 
           {txt}{c |}{res}     17.80      82.20 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
 White GOP {c |}{res}       125        281 {txt}{c |}{res}       406 
           {txt}{c |}{res}     30.79      69.21 {txt}{c |}{res}    100.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       435      1,509 {txt}{c |}{res}     1,944 
           {txt}{c |}{res}     22.38      77.62 {txt}{c |}{res}    100.00 
{txt}
{com}. 
. *****PAIRWISE DIFFERENCE OF PROPORTIONS TESTS (FOR APPENDIX)*****
. foreach y of varlist myrace_DNA2 myrace_DNA morethanone DNAanycon {c -(}
{txt}  2{com}.         disp "TESTS FOR VARIABLE: `y'"
{txt}  3{com}.         foreach v of varlist AB-WDR {c -(}
{txt}  4{com}.                 prtest `y' if `v'==1, by(fivegroups)
{txt}  5{com}.         {c )-}
{txt}  6{com}.         {c )-}
TESTS FOR VARIABLE: myrace_DNA2

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                               Black{txt}: Number of obs = {res}     384
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8806366{col 28}  .016698{col 58} .8479092{col 70}  .913364
       {txt}Black {c |}{res}{col 17}  .859375{col 28} .0177401{col 58}  .824605{col 70}  .894145
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0212616{col 28} .0243626{col 58}-.0264881{col 70} .0690113
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0243903{col 38}    0.87{col 49}0.383
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Black{txt})                          z = {res}  0.8717
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.8083         {txt}Pr(|Z| > |z|) = {res}0.3834          {txt}Pr(Z > z) = {res}0.1917

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8806366{col 28}  .016698{col 58} .8479092{col 70}  .913364
      {txt}Latino {c |}{res}{col 17} .8174387{col 28}  .020165{col 58}  .777916{col 70} .8569614
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0631979{col 28} .0261811{col 58} .0118839{col 70} .1145119
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0262227{col 38}    2.41{col 49}0.016
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Latino{txt})                         z = {res}  2.4100
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9920         {txt}Pr(|Z| > |z|) = {res}0.0160          {txt}Pr(Z > z) = {res}0.0080

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8806366{col 28}  .016698{col 58} .8479092{col 70}  .913364
   {txt}White DEM {c |}{res}{col 17}  .895122{col 28} .0151318{col 58} .8654641{col 70} .9247798
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0144853{col 28} .0225343{col 58}-.0586517{col 70}  .029681
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0224869{col 38}   -0.64{col 49}0.519
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White DEM{txt})                      z = {res} -0.6442
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.2597         {txt}Pr(|Z| > |z|) = {res}0.5195          {txt}Pr(Z > z) = {res}0.7403

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8806366{col 28}  .016698{col 58} .8479092{col 70}  .913364
   {txt}White GOP {c |}{res}{col 17} .8448276{col 28} .0179692{col 58} .8096086{col 70} .8800465
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}  .035809{col 28} .0245298{col 58}-.0122686{col 70} .0838866
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0246632{col 38}    1.45{col 49}0.147
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White GOP{txt})                      z = {res}  1.4519
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9267         {txt}Pr(|Z| > |z|) = {res}0.1465          {txt}Pr(Z > z) = {res}0.0733

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17}  .859375{col 28} .0177401{col 58}  .824605{col 70}  .894145
      {txt}Latino {c |}{res}{col 17} .8174387{col 28}  .020165{col 58}  .777916{col 70} .8569614
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0419363{col 28} .0268578{col 58} -.010704{col 70} .0945766
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0268376{col 38}    1.56{col 49}0.118
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}Latino{txt})                         z = {res}  1.5626
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9409         {txt}Pr(|Z| > |z|) = {res}0.1181          {txt}Pr(Z > z) = {res}0.0591

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17}  .859375{col 28} .0177401{col 58}  .824605{col 70}  .894145
   {txt}White DEM {c |}{res}{col 17}  .895122{col 28} .0151318{col 58} .8654641{col 70} .9247798
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} -.035747{col 28} .0233171{col 58}-.0814475{col 70} .0099536
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28}  .023256{col 38}   -1.54{col 49}0.124
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White DEM{txt})                      z = {res} -1.5371
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0621         {txt}Pr(|Z| > |z|) = {res}0.1243          {txt}Pr(Z > z) = {res}0.9379

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17}  .859375{col 28} .0177401{col 58}  .824605{col 70}  .894145
   {txt}White GOP {c |}{res}{col 17} .8448276{col 28} .0179692{col 58} .8096086{col 70} .8800465
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0145474{col 28} .0252508{col 58}-.0349433{col 70} .0640381
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0252847{col 38}    0.58{col 49}0.565
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White GOP{txt})                      z = {res}  0.5753
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.7175         {txt}Pr(|Z| > |z|) = {res}0.5651          {txt}Pr(Z > z) = {res}0.2825

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .8174387{col 28}  .020165{col 58}  .777916{col 70} .8569614
   {txt}White DEM {c |}{res}{col 17}  .895122{col 28} .0151318{col 58} .8654641{col 70} .9247798
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0776833{col 28} .0252111{col 58}-.1270962{col 70}-.0282704
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0250509{col 38}   -3.10{col 49}0.002
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White DEM{txt})                     z = {res} -3.1010
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0010         {txt}Pr(|Z| > |z|) = {res}0.0019          {txt}Pr(Z > z) = {res}0.9990

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .8174387{col 28}  .020165{col 58}  .777916{col 70} .8569614
   {txt}White GOP {c |}{res}{col 17} .8448276{col 28} .0179692{col 58} .8096086{col 70} .8800465
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0273889{col 28} .0270096{col 58}-.0803268{col 70}  .025549
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0269396{col 38}   -1.02{col 49}0.309
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White GOP{txt})                     z = {res} -1.0167
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.1547         {txt}Pr(|Z| > |z|) = {res}0.3093          {txt}Pr(Z > z) = {res}0.8453

{txt}Two-sample test of proportions             {res}White DEM{txt}: Number of obs = {res}     410
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
   White DEM {c |}{res}{col 17}  .895122{col 28} .0151318{col 58} .8654641{col 70} .9247798
   {txt}White GOP {c |}{res}{col 17} .8448276{col 28} .0179692{col 58} .8096086{col 70} .8800465
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0502944{col 28} .0234918{col 58} .0042513{col 70} .0963374
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0235387{col 38}    2.14{col 49}0.033
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}White DEM{txt}) - prop({res}White GOP{txt})                  z = {res}  2.1367
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9837         {txt}Pr(|Z| > |z|) = {res}0.0326          {txt}Pr(Z > z) = {res}0.0163
TESTS FOR VARIABLE: myrace_DNA

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                               Black{txt}: Number of obs = {res}     384
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .5066313{col 28}  .025749{col 58} .4561641{col 70} .5570985
       {txt}Black {c |}{res}{col 17}     .625{col 28} .0247053{col 58} .5765785{col 70} .6734215
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.1183687{col 28} .0356842{col 58}-.1883085{col 70}-.0484289
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0359308{col 38}   -3.29{col 49}0.001
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Black{txt})                          z = {res} -3.2944
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0005         {txt}Pr(|Z| > |z|) = {res}0.0010          {txt}Pr(Z > z) = {res}0.9995

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .5066313{col 28}  .025749{col 58} .4561641{col 70} .5570985
      {txt}Latino {c |}{res}{col 17} .5013624{col 28} .0260997{col 58} .4502079{col 70} .5525169
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0052689{col 28} .0366634{col 58}-.0665901{col 70} .0771279
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0366639{col 38}    0.14{col 49}0.886
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Latino{txt})                         z = {res}  0.1437
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.5571         {txt}Pr(|Z| > |z|) = {res}0.8857          {txt}Pr(Z > z) = {res}0.4429

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .5066313{col 28}  .025749{col 58} .4561641{col 70} .5570985
   {txt}White DEM {c |}{res}{col 17} .5585366{col 28} .0245234{col 58} .5104715{col 70} .6066016
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0519053{col 28} .0355586{col 58}-.1215988{col 70} .0177882
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0355965{col 38}   -1.46{col 49}0.145
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White DEM{txt})                      z = {res} -1.4582
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0724         {txt}Pr(|Z| > |z|) = {res}0.1448          {txt}Pr(Z > z) = {res}0.9276

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .5066313{col 28}  .025749{col 58} .4561641{col 70} .5570985
   {txt}White GOP {c |}{res}{col 17}   .58867{col 28} .0244213{col 58} .5408052{col 70} .6365347
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0820387{col 28} .0354882{col 58}-.1515942{col 70}-.0124831
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0355883{col 38}   -2.31{col 49}0.021
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White GOP{txt})                      z = {res} -2.3052
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0106         {txt}Pr(|Z| > |z|) = {res}0.0212          {txt}Pr(Z > z) = {res}0.9894

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17}     .625{col 28} .0247053{col 58} .5765785{col 70} .6734215
      {txt}Latino {c |}{res}{col 17} .5013624{col 28} .0260997{col 58} .4502079{col 70} .5525169
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .1236376{col 28} .0359381{col 58} .0532003{col 70} .1940749
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0361941{col 38}    3.42{col 49}0.001
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}Latino{txt})                         z = {res}  3.4160
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9997         {txt}Pr(|Z| > |z|) = {res}0.0006          {txt}Pr(Z > z) = {res}0.0003

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17}     .625{col 28} .0247053{col 58} .5765785{col 70} .6734215
   {txt}White DEM {c |}{res}{col 17} .5585366{col 28} .0245234{col 58} .5104715{col 70} .6066016
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0664634{col 28} .0348102{col 58}-.0017633{col 70} .1346902
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0349189{col 38}    1.90{col 49}0.057
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White DEM{txt})                      z = {res}  1.9034
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9715         {txt}Pr(|Z| > |z|) = {res}0.0570          {txt}Pr(Z > z) = {res}0.0285

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17}     .625{col 28} .0247053{col 58} .5765785{col 70} .6734215
   {txt}White GOP {c |}{res}{col 17}   .58867{col 28} .0244213{col 58} .5408052{col 70} .6365347
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}   .03633{col 28} .0347383{col 58}-.0317558{col 70} .1044159
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0347781{col 38}    1.04{col 49}0.296
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White GOP{txt})                      z = {res}  1.0446
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.8519         {txt}Pr(|Z| > |z|) = {res}0.2962          {txt}Pr(Z > z) = {res}0.1481

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .5013624{col 28} .0260997{col 58} .4502079{col 70} .5525169
   {txt}White DEM {c |}{res}{col 17} .5585366{col 28} .0245234{col 58} .5104715{col 70} .6066016
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0571742{col 28} .0358133{col 58} -.127367{col 70} .0130186
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0358583{col 38}   -1.59{col 49}0.111
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White DEM{txt})                     z = {res} -1.5944
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0554         {txt}Pr(|Z| > |z|) = {res}0.1108          {txt}Pr(Z > z) = {res}0.9446

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .5013624{col 28} .0260997{col 58} .4502079{col 70} .5525169
   {txt}White GOP {c |}{res}{col 17}   .58867{col 28} .0244213{col 58} .5408052{col 70} .6365347
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0873076{col 28} .0357434{col 58}-.1573634{col 70}-.0172517
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0358524{col 38}   -2.44{col 49}0.015
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White GOP{txt})                     z = {res} -2.4352
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0074         {txt}Pr(|Z| > |z|) = {res}0.0149          {txt}Pr(Z > z) = {res}0.9926

{txt}Two-sample test of proportions             {res}White DEM{txt}: Number of obs = {res}     410
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
   White DEM {c |}{res}{col 17} .5585366{col 28} .0245234{col 58} .5104715{col 70} .6066016
   {txt}White GOP {c |}{res}{col 17}   .58867{col 28} .0244213{col 58} .5408052{col 70} .6365347
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0301334{col 28} .0346092{col 58}-.0979662{col 70} .0376994
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0346268{col 38}   -0.87{col 49}0.384
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}White DEM{txt}) - prop({res}White GOP{txt})                  z = {res} -0.8702
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.1921         {txt}Pr(|Z| > |z|) = {res}0.3842          {txt}Pr(Z > z) = {res}0.8079
TESTS FOR VARIABLE: morethanone

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                               Black{txt}: Number of obs = {res}     384
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .9655172{col 28} .0093975{col 58} .9470986{col 70} .9839359
       {txt}Black {c |}{res}{col 17} .9427083{col 28} .0118596{col 58}  .919464{col 70} .9659527
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0228089{col 28} .0151315{col 58}-.0068482{col 70} .0524661
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0151871{col 38}    1.50{col 49}0.133
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Black{txt})                          z = {res}  1.5019
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9334         {txt}Pr(|Z| > |z|) = {res}0.1331          {txt}Pr(Z > z) = {res}0.0666

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .9655172{col 28} .0093975{col 58} .9470986{col 70} .9839359
      {txt}Latino {c |}{res}{col 17} .9100817{col 28} .0149325{col 58} .8808147{col 70} .9393488
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0554355{col 28} .0176434{col 58}  .020855{col 70}  .090016
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28}  .017661{col 38}    3.14{col 49}0.002
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Latino{txt})                         z = {res}  3.1389
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9992         {txt}Pr(|Z| > |z|) = {res}0.0017          {txt}Pr(Z > z) = {res}0.0008

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .9655172{col 28} .0093975{col 58} .9470986{col 70} .9839359
   {txt}White DEM {c |}{res}{col 17} .9292683{col 28} .0126615{col 58} .9044522{col 70} .9540844
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0362489{col 28} .0157679{col 58} .0053445{col 70} .0671534
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0160381{col 38}    2.26{col 49}0.024
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White DEM{txt})                      z = {res}  2.2602
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9881         {txt}Pr(|Z| > |z|) = {res}0.0238          {txt}Pr(Z > z) = {res}0.0119

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .9655172{col 28} .0093975{col 58} .9470986{col 70} .9839359
   {txt}White GOP {c |}{res}{col 17} .8817734{col 28} .0160241{col 58} .8503668{col 70}   .91318
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0837438{col 28} .0185764{col 58} .0473347{col 70}  .120153
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0191699{col 38}    4.37{col 49}0.000
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White GOP{txt})                      z = {res}  4.3685
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}1.0000         {txt}Pr(|Z| > |z|) = {res}0.0000          {txt}Pr(Z > z) = {res}0.0000

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17} .9427083{col 28} .0118596{col 58}  .919464{col 70} .9659527
      {txt}Latino {c |}{res}{col 17} .9100817{col 28} .0149325{col 58} .8808147{col 70} .9393488
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0326266{col 28}  .019069{col 58} -.004748{col 70} .0700012
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0190181{col 38}    1.72{col 49}0.086
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}Latino{txt})                         z = {res}  1.7156
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9569         {txt}Pr(|Z| > |z|) = {res}0.0862          {txt}Pr(Z > z) = {res}0.0431

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17} .9427083{col 28} .0118596{col 58}  .919464{col 70} .9659527
   {txt}White DEM {c |}{res}{col 17} .9292683{col 28} .0126615{col 58} .9044522{col 70} .9540844
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}   .01344{col 28} .0173483{col 58} -.020562{col 70} .0474421
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0174105{col 38}    0.77{col 49}0.440
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White DEM{txt})                      z = {res}  0.7719
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.7799         {txt}Pr(|Z| > |z|) = {res}0.4401          {txt}Pr(Z > z) = {res}0.2201

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17} .9427083{col 28} .0118596{col 58}  .919464{col 70} .9659527
   {txt}White GOP {c |}{res}{col 17} .8817734{col 28} .0160241{col 58} .8503668{col 70}   .91318
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0609349{col 28} .0199354{col 58} .0218623{col 70} .1000076
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0202289{col 38}    3.01{col 49}0.003
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White GOP{txt})                      z = {res}  3.0123
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9987         {txt}Pr(|Z| > |z|) = {res}0.0026          {txt}Pr(Z > z) = {res}0.0013

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .9100817{col 28} .0149325{col 58} .8808147{col 70} .9393488
   {txt}White DEM {c |}{res}{col 17} .9292683{col 28} .0126615{col 58} .9044522{col 70} .9540844
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0191865{col 28} .0195778{col 58}-.0575584{col 70} .0191853
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0194721{col 38}   -0.99{col 49}0.324
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White DEM{txt})                     z = {res} -0.9853
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.1622         {txt}Pr(|Z| > |z|) = {res}0.3245          {txt}Pr(Z > z) = {res}0.8378

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .9100817{col 28} .0149325{col 58} .8808147{col 70} .9393488
   {txt}White GOP {c |}{res}{col 17} .8817734{col 28} .0160241{col 58} .8503668{col 70}   .91318
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0283083{col 28} .0219032{col 58}-.0146211{col 70} .0712378
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0220602{col 38}    1.28{col 49}0.199
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White GOP{txt})                     z = {res}  1.2832
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9003         {txt}Pr(|Z| > |z|) = {res}0.1994          {txt}Pr(Z > z) = {res}0.0997

{txt}Two-sample test of proportions             {res}White DEM{txt}: Number of obs = {res}     410
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
   White DEM {c |}{res}{col 17} .9292683{col 28} .0126615{col 58} .9044522{col 70} .9540844
   {txt}White GOP {c |}{res}{col 17} .8817734{col 28} .0160241{col 58} .8503668{col 70}   .91318
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0474949{col 28} .0204227{col 58} .0074672{col 70} .0875226
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0204676{col 38}    2.32{col 49}0.020
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}White DEM{txt}) - prop({res}White GOP{txt})                  z = {res}  2.3205
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9898         {txt}Pr(|Z| > |z|) = {res}0.0203          {txt}Pr(Z > z) = {res}0.0102
TESTS FOR VARIABLE: DNAanycon

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                               Black{txt}: Number of obs = {res}     384
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8222812{col 28} .0196882{col 58}  .783693{col 70} .8608693
       {txt}Black {c |}{res}{col 17} .7890625{col 28} .0208193{col 58} .7482573{col 70} .8298677
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0332187{col 28} .0286543{col 58}-.0229428{col 70} .0893801
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0286967{col 38}    1.16{col 49}0.247
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Black{txt})                          z = {res}  1.1576
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.8765         {txt}Pr(|Z| > |z|) = {res}0.2470          {txt}Pr(Z > z) = {res}0.1235

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8222812{col 28} .0196882{col 58}  .783693{col 70} .8608693
      {txt}Latino {c |}{res}{col 17} .7574932{col 28} .0223727{col 58} .7136435{col 70} .8013429
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}  .064788{col 28} .0298021{col 58}  .006377{col 70}  .123199
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0298511{col 38}    2.17{col 49}0.030
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}Latino{txt})                         z = {res}  2.1704
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9850         {txt}Pr(|Z| > |z|) = {res}0.0300          {txt}Pr(Z > z) = {res}0.0150

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8222812{col 28} .0196882{col 58}  .783693{col 70} .8608693
   {txt}White DEM {c |}{res}{col 17} .8219512{col 28}  .018893{col 58} .7849216{col 70} .8589808
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0003299{col 28} .0272868{col 58}-.0531512{col 70} .0538111
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0272877{col 38}    0.01{col 49}0.990
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White DEM{txt})                      z = {res}  0.0121
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.5048         {txt}Pr(|Z| > |z|) = {res}0.9904          {txt}Pr(Z > z) = {res}0.4952

{txt}Two-sample test of proportions                 {res}Asian{txt}: Number of obs = {res}     377
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Asian {c |}{res}{col 17} .8222812{col 28} .0196882{col 58}  .783693{col 70} .8608693
   {txt}White GOP {c |}{res}{col 17} .6921182{col 28} .0229097{col 58} .6472161{col 70} .7370204
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .1301629{col 28} .0302073{col 58} .0709578{col 70} .1893681
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0307702{col 38}    4.23{col 49}0.000
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Asian{txt}) - prop({res}White GOP{txt})                      z = {res}  4.2302
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}1.0000         {txt}Pr(|Z| > |z|) = {res}0.0000          {txt}Pr(Z > z) = {res}0.0000

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                              Latino{txt}: Number of obs = {res}     367
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17} .7890625{col 28} .0208193{col 58} .7482573{col 70} .8298677
      {txt}Latino {c |}{res}{col 17} .7574932{col 28} .0223727{col 58} .7136435{col 70} .8013429
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0315693{col 28} .0305611{col 58}-.0283294{col 70}  .091468
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0305488{col 38}    1.03{col 49}0.301
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}Latino{txt})                         z = {res}  1.0334
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.8493         {txt}Pr(|Z| > |z|) = {res}0.3014          {txt}Pr(Z > z) = {res}0.1507

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17} .7890625{col 28} .0208193{col 58} .7482573{col 70} .8298677
   {txt}White DEM {c |}{res}{col 17} .8219512{col 28}  .018893{col 58} .7849216{col 70} .8589808
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0328887{col 28} .0281139{col 58}-.0879909{col 70} .0222135
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0280791{col 38}   -1.17{col 49}0.241
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White DEM{txt})                      z = {res} -1.1713
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.1207         {txt}Pr(|Z| > |z|) = {res}0.2415          {txt}Pr(Z > z) = {res}0.8793

{txt}Two-sample test of proportions                 {res}Black{txt}: Number of obs = {res}     384
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
       Black {c |}{res}{col 17} .7890625{col 28} .0208193{col 58} .7482573{col 70} .8298677
   {txt}White GOP {c |}{res}{col 17} .6921182{col 28} .0229097{col 58} .6472161{col 70} .7370204
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0969443{col 28} .0309564{col 58} .0362708{col 70} .1576177
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0312534{col 38}    3.10{col 49}0.002
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Black{txt}) - prop({res}White GOP{txt})                      z = {res}  3.1019
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9990         {txt}Pr(|Z| > |z|) = {res}0.0019          {txt}Pr(Z > z) = {res}0.0010

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White DEM{txt}: Number of obs = {res}     410
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .7574932{col 28} .0223727{col 58} .7136435{col 70} .8013429
   {txt}White DEM {c |}{res}{col 17} .8219512{col 28}  .018893{col 58} .7849216{col 70} .8589808
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} -.064458{col 28} .0292828{col 58}-.1218513{col 70}-.0070648
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0291917{col 38}   -2.21{col 49}0.027
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White DEM{txt})                     z = {res} -2.2081
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0136         {txt}Pr(|Z| > |z|) = {res}0.0272          {txt}Pr(Z > z) = {res}0.9864

{txt}Two-sample test of proportions                {res}Latino{txt}: Number of obs = {res}     367
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
      Latino {c |}{res}{col 17} .7574932{col 28} .0223727{col 58} .7136435{col 70} .8013429
   {txt}White GOP {c |}{res}{col 17} .6921182{col 28} .0229097{col 58} .6472161{col 70} .7370204
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}  .065375{col 28} .0320217{col 58} .0026135{col 70} .1281364
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0322275{col 38}    2.03{col 49}0.043
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}Latino{txt}) - prop({res}White GOP{txt})                     z = {res}  2.0285
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9787         {txt}Pr(|Z| > |z|) = {res}0.0425          {txt}Pr(Z > z) = {res}0.0213

{txt}Two-sample test of proportions             {res}White DEM{txt}: Number of obs = {res}     410
                                           White GOP{txt}: Number of obs = {res}     406
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
   White DEM {c |}{res}{col 17} .8219512{col 28}  .018893{col 58} .7849216{col 70} .8589808
   {txt}White GOP {c |}{res}{col 17} .6921182{col 28} .0229097{col 58} .6472161{col 70} .7370204
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}  .129833{col 28} .0296951{col 58} .0716317{col 70} .1880343
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0300142{col 38}    4.33{col 49}0.000
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}White DEM{txt}) - prop({res}White GOP{txt})                  z = {res}  4.3257
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}1.0000         {txt}Pr(|Z| > |z|) = {res}0.0000          {txt}Pr(Z > z) = {res}0.0000
{txt}
{com}. 
. **********START FIGURE 2**********
. foreach y of varlist morethanone DNAanycon {c -(}
{txt}  2{com}. tempname memhold
{txt}  3{com}. tempfile `y'
{txt}  4{com}. postfile `memhold' fivegroups propagree seprop using `y', replace
{txt}  5{com}. forval v=1/5 {c -(}
{txt}  6{com}.         reg `y' if fivegroups==`v'
{txt}  7{com}.         post `memhold ' (`v') (_b[_cons]) (_se[_cons])
{txt}  8{com}. {c )-}
{txt}  9{com}. postclose `memhold'
{txt} 10{com}. {c )-}
{txt}{p 0 4 2}
(file {bf}
morethanone.dta{rm}
not found)
{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       377
{txt}{hline 13}{c +}{hline 34}   F(0, 376)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 12.5517241       376  .033382245   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 12.5517241       376  .033382245   {txt}Root MSE        =   {res} .18271

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} morethanone{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .9655172{col 26}{space 2} .0094099{col 37}{space 1}  102.61{col 46}{space 3}0.000{col 54}{space 4} .9470145{col 67}{space 3}   .98402
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       384
{txt}{hline 13}{c +}{hline 34}   F(0, 383)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 20.7395833       383  .054150348   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 20.7395833       383  .054150348   {txt}Root MSE        =   {res}  .2327

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} morethanone{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .9427083{col 26}{space 2}  .011875{col 37}{space 1}   79.39{col 46}{space 3}0.000{col 54}{space 4} .9193599{col 67}{space 3} .9660568
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       367
{txt}{hline 13}{c +}{hline 34}   F(0, 366)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 30.0326975       366  .082056551   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 30.0326975       366  .082056551   {txt}Root MSE        =   {res} .28646

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} morethanone{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .9100817{col 26}{space 2} .0149528{col 37}{space 1}   60.86{col 46}{space 3}0.000{col 54}{space 4} .8806775{col 67}{space 3}  .939486
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       410
{txt}{hline 13}{c +}{hline 34}   F(0, 409)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 26.9487805       409  .065889439   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 26.9487805       409  .065889439   {txt}Root MSE        =   {res} .25669

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} morethanone{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .9292683{col 26}{space 2}  .012677{col 37}{space 1}   73.30{col 46}{space 3}0.000{col 54}{space 4} .9043481{col 67}{space 3} .9541885
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       406
{txt}{hline 13}{c +}{hline 34}   F(0, 405)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 42.3251232       405  .104506477   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 42.3251232       405  .104506477   {txt}Root MSE        =   {res} .32327

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} morethanone{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .8817734{col 26}{space 2} .0160438{col 37}{space 1}   54.96{col 46}{space 3}0.000{col 54}{space 4} .8502338{col 67}{space 3}  .913313
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
(file {bf}
DNAanycon.dta{rm}
not found)
{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       377
{txt}{hline 13}{c +}{hline 34}   F(0, 376)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 55.0928382       376  .146523506   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 55.0928382       376  .146523506   {txt}Root MSE        =   {res} .38278

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   DNAanycon{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .8222812{col 26}{space 2} .0197144{col 37}{space 1}   41.71{col 46}{space 3}0.000{col 54}{space 4} .7835169{col 67}{space 3} .8610454
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       384
{txt}{hline 13}{c +}{hline 34}   F(0, 383)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 63.9140625       383  .166877448   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 63.9140625       383  .166877448   {txt}Root MSE        =   {res} .40851

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   DNAanycon{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .7890625{col 26}{space 2} .0208465{col 37}{space 1}   37.85{col 46}{space 3}0.000{col 54}{space 4} .7480746{col 67}{space 3} .8300504
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       367
{txt}{hline 13}{c +}{hline 34}   F(0, 366)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 67.4168937       366  .184199163   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 67.4168937       366  .184199163   {txt}Root MSE        =   {res} .42918

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   DNAanycon{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .7574932{col 26}{space 2} .0224032{col 37}{space 1}   33.81{col 46}{space 3}0.000{col 54}{space 4}  .713438{col 67}{space 3} .8015484
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       410
{txt}{hline 13}{c +}{hline 34}   F(0, 409)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}  60.002439       409   .14670523   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res}  60.002439       409   .14670523   {txt}Root MSE        =   {res} .38302

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   DNAanycon{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .8219512{col 26}{space 2} .0189161{col 37}{space 1}   43.45{col 46}{space 3}0.000{col 54}{space 4} .7847664{col 67}{space 3} .8591361
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       406
{txt}{hline 13}{c +}{hline 34}   F(0, 405)       = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res} 86.5147783       405  .213616737   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0000
{txt}       Total {c |} {res} 86.5147783       405  .213616737   {txt}Root MSE        =   {res} .46219

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   DNAanycon{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .6921182{col 26}{space 2}  .022938{col 37}{space 1}   30.17{col 46}{space 3}0.000{col 54}{space 4} .6470259{col 67}{space 3} .7372105
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. preserve
{txt}
{com}. use morethanone, clear
{txt}
{com}. lab def fivegroups 1"Asian" 2"Black" 3"Latino" 4"White DEM" 5"White GOP"
{txt}
{com}. lab val fivegroups fivegroups
{txt}
{com}. gen UB = propagree + 1.96*seprop
{txt}
{com}. gen LB = propagree - 1.96*seprop
{txt}
{com}. twoway (bar propagree fivegroups, fcolor(gs8)) (rcap UB LB fivegroups, lcolor(black)), xlabel(, valuelabel) xtitle(" ") legend(off) ylabel(0(.25)1) title("(a) Proportion Agree with >1 Factor to Define Race") name(morethanone, replace)
{res}{txt}
{com}. 
. use DNAanycon, clear
{txt}
{com}. lab def fivegroups 1"Asian" 2"Black" 3"Latino" 4"White DEM" 5"White GOP"
{txt}
{com}. lab val fivegroups fivegroups
{txt}
{com}. gen UB = propagree + 1.96*seprop
{txt}
{com}. gen LB = propagree - 1.96*seprop
{txt}
{com}. twoway (bar propagree fivegroups, fcolor(gs8)) (rcap UB LB fivegroups, lcolor(black)), xlabel(, valuelabel) xtitle(" ") legend(off) ylabel(0(.25)1) title("(b) Proportion Agree with 'Conflicting' Factors to Define Race") name(DNAanycon, replace)
{res}{txt}
{com}. 
. graph combine morethanone DNAanycon, row(1) col(2) iscale(.7) imargin(r+10 l+5) xsize(6.5) ysize(2.5) 
{res}{txt}
{com}. graph export Figure2.pdf, replace
{txt}{p 0 4 2}
file {bf}
Figure2.pdf{rm}
saved as
PDF
format
{p_end}

{com}. restore
{txt}
{com}. **********END FIGURE 2**********
. *****cleaning up directory*****
. erase DNAanycon.dta
{txt}
{com}. erase morethanone.dta 
{txt}
{com}. 
. **********BIOLOGICAL DETERMINISM**********
. recode moduleC_scale (1=1 "All biology")(2=.75)(3=.5)(4=.25)(5=0 "Identity totally separate")(else=.), gen(race_bio_identity)
{txt}(1,419 differences between {bf:moduleC_scale} and {bf:race_bio_identity})

{com}. 
. gen race_bio_graph= -1*(moduleC_scale-5)
{txt}
{com}. lab def race_bio_graph 0 "Racial identity is totally separate from biology" 1 "Racial identity is somewhat separate from biology" 2 "Racial identity is tied to your biology but not determined by it" 3 "Biology somewhat determines your racial identity" 4 "Biology totally determines your racial identity", modify
{txt}
{com}. lab val race_bio_graph race_bio_graph
{txt}
{com}. 
. *****in text*****
. tab race_bio_graph fivegroups, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

                      {c |}                       Subgroups
       race_bio_graph {c |}     Asian      Black     Latino  White DEM  White GOP {c |}     Total
{hline 22}{c +}{hline 55}{c +}{hline 10}
Racial identity is to {c |}{res}        36         56         50         36         50 {txt}{c |}{res}       228 
                      {txt}{c |}{res}      9.55      14.58      13.62       8.78      12.32 {txt}{c |}{res}     11.73 
{txt}{hline 22}{c +}{hline 55}{c +}{hline 10}
Racial identity is so {c |}{res}        15         31         32         34         20 {txt}{c |}{res}       132 
                      {txt}{c |}{res}      3.98       8.07       8.72       8.29       4.93 {txt}{c |}{res}      6.79 
{txt}{hline 22}{c +}{hline 55}{c +}{hline 10}
Racial identity is ti {c |}{res}       118        130        114        126        114 {txt}{c |}{res}       602 
                      {txt}{c |}{res}     31.30      33.85      31.06      30.73      28.08 {txt}{c |}{res}     30.97 
{txt}{hline 22}{c +}{hline 55}{c +}{hline 10}
Biology somewhat dete {c |}{res}       121         69         74         96         74 {txt}{c |}{res}       434 
                      {txt}{c |}{res}     32.10      17.97      20.16      23.41      18.23 {txt}{c |}{res}     22.33 
{txt}{hline 22}{c +}{hline 55}{c +}{hline 10}
Biology totally deter {c |}{res}        87         98         97        118        148 {txt}{c |}{res}       548 
                      {txt}{c |}{res}     23.08      25.52      26.43      28.78      36.45 {txt}{c |}{res}     28.19 
{txt}{hline 22}{c +}{hline 55}{c +}{hline 10}
                Total {c |}{res}       377        384        367        410        406 {txt}{c |}{res}     1,944 
                      {txt}{c |}{res}    100.00     100.00     100.00     100.00     100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. *range on somewhat + totally, Low & Hi: 34 to 55%
. disp 17.97+25.52
{res}43.49
{txt}
{com}. disp 32.10+23.08
{res}55.18
{txt}
{com}. 
. *****PAIRWISE DIFFERENCE OF MEANS TESTS
. foreach v of varlist AB-WDR {c -(}
{txt}  2{com}.                 ttest race_bio_identity if `v'==1, by(fivegroups)
{txt}  3{com}.         {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
   Asian {c |}{res}{col 12}    377{col 22}  .637931{col 34} .0150431{col 46} .2920834{col 58}  .608352{col 70} .6675101
   {txt}Black {c |}{res}{col 12}    384{col 22} .5794271{col 34} .0169647{col 46} .3324389{col 58} .5460715{col 70} .6127827
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    761{col 22}   .60841{col 34} .0113918{col 46} .3142581{col 58} .5860468{col 70} .6307732
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}  .058504{col 34} .0227006{col 58} .0139406{col 70} .1030673
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Asian{txt}) - mean({res}Black{txt})                              t = {res}  2.5772
{txt}H0: diff = 0                                     Degrees of freedom = {res}     759

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9949         {txt}Pr(|T| > |t|) = {res}0.0101          {txt}Pr(T > t) = {res}0.0051

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
   Asian {c |}{res}{col 12}    377{col 22}  .637931{col 34} .0150431{col 46} .2920834{col 58}  .608352{col 70} .6675101
  {txt}Latino {c |}{res}{col 12}    367{col 22} .5926431{col 34} .0173051{col 46} .3315188{col 58} .5586131{col 70}  .626673
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    744{col 22} .6155914{col 34} .0114667{col 46} .3127702{col 58} .5930804{col 70} .6381024
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}  .045288{col 34} .0228907{col 58} .0003498{col 70} .0902261
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Asian{txt}) - mean({res}Latino{txt})                             t = {res}  1.9784
{txt}H0: diff = 0                                     Degrees of freedom = {res}     742

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9759         {txt}Pr(|T| > |t|) = {res}0.0482          {txt}Pr(T > t) = {res}0.0241

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
   Asian {c |}{res}{col 12}    377{col 22}  .637931{col 34} .0150431{col 46} .2920834{col 58}  .608352{col 70} .6675101
{txt}White DE {c |}{res}{col 12}    410{col 22} .6378049{col 34} .0152188{col 46} .3081573{col 58}  .607888{col 70} .6677217
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    787{col 22} .6378653{col 34} .0107072{col 46} .3003743{col 58} .6168472{col 70} .6588834
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0001262{col 34} .0214469{col 58}-.0419738{col 70} .0422262
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Asian{txt}) - mean({res}White DE{txt})                           t = {res}  0.0059
{txt}H0: diff = 0                                     Degrees of freedom = {res}     785

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.5023         {txt}Pr(|T| > |t|) = {res}0.9953          {txt}Pr(T > t) = {res}0.4977

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
   Asian {c |}{res}{col 12}    377{col 22}  .637931{col 34} .0150431{col 46} .2920834{col 58}  .608352{col 70} .6675101
{txt}White GO {c |}{res}{col 12}    406{col 22} .6539409{col 34}  .016681{col 46} .3361132{col 58} .6211487{col 70} .6867331
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    783{col 22} .6462324{col 34}  .011278{col 46} .3155829{col 58} .6240937{col 70} .6683712
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0160099{col 34} .0225787{col 58} -.060332{col 70} .0283123
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Asian{txt}) - mean({res}White GO{txt})                           t = {res} -0.7091
{txt}H0: diff = 0                                     Degrees of freedom = {res}     781

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.2392         {txt}Pr(|T| > |t|) = {res}0.4785          {txt}Pr(T > t) = {res}0.7608

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
   Black {c |}{res}{col 12}    384{col 22} .5794271{col 34} .0169647{col 46} .3324389{col 58} .5460715{col 70} .6127827
  {txt}Latino {c |}{res}{col 12}    367{col 22} .5926431{col 34} .0173051{col 46} .3315188{col 58} .5586131{col 70}  .626673
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    751{col 22} .5858855{col 34} .0121088{col 46} .3318341{col 58} .5621143{col 70} .6096567
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} -.013216{col 34} .0242352{col 58}-.0607929{col 70} .0343609
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Black{txt}) - mean({res}Latino{txt})                             t = {res} -0.5453
{txt}H0: diff = 0                                     Degrees of freedom = {res}     749

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.2928         {txt}Pr(|T| > |t|) = {res}0.5857          {txt}Pr(T > t) = {res}0.7072

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
   Black {c |}{res}{col 12}    384{col 22} .5794271{col 34} .0169647{col 46} .3324389{col 58} .5460715{col 70} .6127827
{txt}White DE {c |}{res}{col 12}    410{col 22} .6378049{col 34} .0152188{col 46} .3081573{col 58}  .607888{col 70} .6677217
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    794{col 22} .6095718{col 34}  .011401{col 46} .3212567{col 58} .5871921{col 70} .6319514
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0583778{col 34} .0227341{col 58}-.1030041{col 70}-.0137515
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Black{txt}) - mean({res}White DE{txt})                           t = {res} -2.5678
{txt}H0: diff = 0                                     Degrees of freedom = {res}     792

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0052         {txt}Pr(|T| > |t|) = {res}0.0104          {txt}Pr(T > t) = {res}0.9948

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
   Black {c |}{res}{col 12}    384{col 22} .5794271{col 34} .0169647{col 46} .3324389{col 58} .5460715{col 70} .6127827
{txt}White GO {c |}{res}{col 12}    406{col 22} .6539409{col 34}  .016681{col 46} .3361132{col 58} .6211487{col 70} .6867331
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    790{col 22} .6177215{col 34} .0119612{col 46} .3361922{col 58}  .594242{col 70}  .641201
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0745138{col 34} .0237993{col 58}-.1212312{col 70}-.0277964
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Black{txt}) - mean({res}White GO{txt})                           t = {res} -3.1309
{txt}H0: diff = 0                                     Degrees of freedom = {res}     788

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0009         {txt}Pr(|T| > |t|) = {res}0.0018          {txt}Pr(T > t) = {res}0.9991

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
  Latino {c |}{res}{col 12}    367{col 22} .5926431{col 34} .0173051{col 46} .3315188{col 58} .5586131{col 70}  .626673
{txt}White DE {c |}{res}{col 12}    410{col 22} .6378049{col 34} .0152188{col 46} .3081573{col 58}  .607888{col 70} .6677217
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    777{col 22} .6164736{col 34} .0114797{col 46} .3199934{col 58} .5939387{col 70} .6390086
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0451618{col 34} .0229522{col 58}-.0902177{col 70} -.000106
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Latino{txt}) - mean({res}White DE{txt})                          t = {res} -1.9676
{txt}H0: diff = 0                                     Degrees of freedom = {res}     775

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0247         {txt}Pr(|T| > |t|) = {res}0.0495          {txt}Pr(T > t) = {res}0.9753

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
  Latino {c |}{res}{col 12}    367{col 22} .5926431{col 34} .0173051{col 46} .3315188{col 58} .5586131{col 70}  .626673
{txt}White GO {c |}{res}{col 12}    406{col 22} .6539409{col 34}  .016681{col 46} .3361132{col 58} .6211487{col 70} .6867331
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    773{col 22} .6248383{col 34} .0120537{col 46} .3351264{col 58} .6011765{col 70} .6485001
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0612978{col 34} .0240526{col 58}-.1085142{col 70}-.0140815
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}Latino{txt}) - mean({res}White GO{txt})                          t = {res} -2.5485
{txt}H0: diff = 0                                     Degrees of freedom = {res}     771

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0055         {txt}Pr(|T| > |t|) = {res}0.0110          {txt}Pr(T > t) = {res}0.9945

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
White DE {c |}{res}{col 12}    410{col 22} .6378049{col 34} .0152188{col 46} .3081573{col 58}  .607888{col 70} .6677217
{txt}White GO {c |}{res}{col 12}    406{col 22} .6539409{col 34}  .016681{col 46} .3361132{col 58} .6211487{col 70} .6867331
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    816{col 22} .6458333{col 34} .0112818{col 46}  .322273{col 58} .6236885{col 70} .6679782
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} -.016136{col 34} .0225707{col 58}-.0604396{col 70} .0281676
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}White DE{txt}) - mean({res}White GO{txt})                        t = {res} -0.7149
{txt}H0: diff = 0                                     Degrees of freedom = {res}     814

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.2374         {txt}Pr(|T| > |t|) = {res}0.4749          {txt}Pr(T > t) = {res}0.7626
{txt}
{com}. 
. **********START FIGURE 3**********      
. catplot, over(race_bio_identity) over(fivegroups) percent(fivegroups) recast(hbar) stack asyvars legend(lab(1 "Racial identity totally separate from biology") lab(2 "Racial identity somewhat separate from biology") lab(3 "Racial identity is tied to your biology but not determined by it") lab(4 "Biology somewhat determines your racial identity") lab(5 "Biology totally determines your racial identity") row(5)) xsize(8) ysize(7) legend(size(*.7))
{res}{txt}
{com}. graph export Figure3.pdf, replace
{txt}{p 0 4 2}
file {bf}
Figure3.pdf{rm}
saved as
PDF
format
{p_end}

{com}. **********END FIGURE 3**********
. 
. **********COVID-19 ATTRIBUTIONS**********
. recode ModuleB_a ModuleB_b ModuleB_c ModuleB_d ModuleB_e ModuleB_f (1=1)(2=.67)(3=.33)(4=0)(else=.), gen(covid_gene covid_preexisting covid_jobs covid_healthcare covid_neighborhood covid_flout_protocols)
{txt}(1,260 differences between {bf:ModuleB_a} and {bf:covid_gene})
(868 differences between {bf:ModuleB_b} and {bf:covid_preexisting})
(949 differences between {bf:ModuleB_c} and {bf:covid_jobs})
(945 differences between {bf:ModuleB_d} and {bf:covid_healthcare})
(963 differences between {bf:ModuleB_e} and {bf:covid_neighborhood})
(985 differences between {bf:ModuleB_f} and {bf:covid_flout_protocols})

{com}. 
. /*Taking out those who refuse the entire battery*/
. egen ref_covid_battery = anycount(ModuleB_a-ModuleB_f), val(4)
{txt}
{com}. tab ref_covid_battery

  {txt}ModuleB_a {c |}
  ModuleB_b {c |}
  ModuleB_c {c |}
  ModuleB_d {c |}
  ModuleB_e {c |}
  ModuleB_f {c |}
       == 4 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}      1,630       82.53       82.53
{txt}          1 {c |}{res}        199       10.08       92.61
{txt}          2 {c |}{res}         70        3.54       96.15
{txt}          3 {c |}{res}         25        1.27       97.42
{txt}          4 {c |}{res}         20        1.01       98.43
{txt}          5 {c |}{res}          8        0.41       98.84
{txt}          6 {c |}{res}         23        1.16      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,975      100.00
{txt}
{com}. //23 people refused to acknowledge any of the factors as accounting for racial disparities
. 
. **********START FIGURE 4**********
. /*ANALYSES WITH RAKED WEIGHTS*/
. //creating weight - survey raking
. //adjust for the five groups
. //using CES 2021 as the benchmark for controls
. 
. svycal regress i.fivegroup, generate(fivegroup_weight) totals(909 3301 3320 6144 7508 21182, copy)
{res}{txt}
{com}. svyset [pweight=fivegroup_weight]

{txt}Sampling weights:{col 19}{res}fivegroup_weight
             {txt}VCE:{col 19}{res}linearized
     {txt}Single unit:{col 19}{res}missing
        {txt}Strata 1:{col 19}<one>
 Sampling unit 1:{col 19}<observations>
           FPC 1:{col 19}<zero>
{p2colreset}{...}

{com}. recode fivegroups (4=1)(1/3 5=0)(else=.), gen(WDem)
{txt}(1,944 differences between {bf:fivegroups} and {bf:WDem})

{com}. recode fivegroups (5=1)(1/4 =0)(else=.), gen(WRep)
{txt}(1,944 differences between {bf:fivegroups} and {bf:WRep})

{com}. 
. foreach v of varlist covid_gene covid_preexisting covid_jobs covid_healthcare covid_neighborhood covid_flout_protocols {c -(}
{txt}  2{com}. svy: reg `v' race_bio_identity pid7cata ed6cat age01 black hispanic api WDem if ref_covid_battery~=6
{txt}  3{com}. est store `v'_wt
{txt}  4{com}. {c )-}
{res}{txt}(running {bf:regress} on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 5:1}{txt}{col 51}{lalign 15:Number of obs}{col 66} = {res}{ralign 10:1,917}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 5:1,917}{txt}{col 51}{lalign 15:Population size}{col 66} = {res}{ralign 10:20,895.419}
{txt}{col 51}{lalign 15:Design df}{col 66} = {res}{ralign 10:1,916}
{txt}{col 51}{lalign 15:F({res:8}, {res:1909})}{col 66} = {res}{ralign 10:9.90}
{txt}{col 51}{lalign 15:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 51}{lalign 15:R-squared}{col 66} = {res}{ralign 10:0.0351}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}  Linearized
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0984333{col 31}{space 2} .0271588{col 42}{space 1}    3.62{col 51}{space 3}0.000{col 59}{space 4} .0451693{col 72}{space 3} .1516973
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1551406{col 31}{space 2} .0353237{col 42}{space 1}   -4.39{col 51}{space 3}0.000{col 59}{space 4}-.2244175{col 72}{space 3}-.0858637
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0795426{col 31}{space 2} .0259623{col 42}{space 1}   -3.06{col 51}{space 3}0.002{col 59}{space 4}  -.13046{col 72}{space 3}-.0286252
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0272224{col 31}{space 2} .0358219{col 42}{space 1}   -0.76{col 51}{space 3}0.447{col 59}{space 4}-.0974764{col 72}{space 3} .0430315
{txt}{space 12}black {c |}{col 19}{res}{space 2} -.019797{col 31}{space 2} .0350534{col 42}{space 1}   -0.56{col 51}{space 3}0.572{col 59}{space 4}-.0885439{col 72}{space 3} .0489498
{txt}{space 9}hispanic {c |}{col 19}{res}{space 2}-.0263574{col 31}{space 2} .0321397{col 42}{space 1}   -0.82{col 51}{space 3}0.412{col 59}{space 4}  -.08939{col 72}{space 3} .0366751
{txt}{space 14}api {c |}{col 19}{res}{space 2}-.0952978{col 31}{space 2} .0299959{col 42}{space 1}   -3.18{col 51}{space 3}0.002{col 59}{space 4} -.154126{col 72}{space 3}-.0364697
{txt}{space 13}WDem {c |}{col 19}{res}{space 2} -.085005{col 31}{space 2} .0368552{col 42}{space 1}   -2.31{col 51}{space 3}0.021{col 59}{space 4}-.1572855{col 72}{space 3}-.0127245
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7618239{col 31}{space 2} .0453413{col 42}{space 1}   16.80{col 51}{space 3}0.000{col 59}{space 4} .6729004{col 72}{space 3} .8507474
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(running {bf:regress} on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 5:1}{txt}{col 51}{lalign 15:Number of obs}{col 66} = {res}{ralign 10:1,918}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 5:1,918}{txt}{col 51}{lalign 15:Population size}{col 66} = {res}{ralign 10:20,904.465}
{txt}{col 51}{lalign 15:Design df}{col 66} = {res}{ralign 10:1,917}
{txt}{col 51}{lalign 15:F({res:8}, {res:1910})}{col 66} = {res}{ralign 10:8.07}
{txt}{col 51}{lalign 15:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 51}{lalign 15:R-squared}{col 66} = {res}{ralign 10:0.0383}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}  Linearized
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0037678{col 31}{space 2} .0203518{col 42}{space 1}    0.19{col 51}{space 3}0.853{col 59}{space 4}-.0361462{col 72}{space 3} .0436817
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0842752{col 31}{space 2}  .026809{col 42}{space 1}   -3.14{col 51}{space 3}0.002{col 59}{space 4}-.1368531{col 72}{space 3}-.0316972
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0272085{col 31}{space 2}  .019786{col 42}{space 1}    1.38{col 51}{space 3}0.169{col 59}{space 4}-.0115958{col 72}{space 3} .0660127
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0930023{col 31}{space 2} .0275264{col 42}{space 1}    3.38{col 51}{space 3}0.001{col 59}{space 4} .0390173{col 72}{space 3} .1469872
{txt}{space 12}black {c |}{col 19}{res}{space 2} .0464504{col 31}{space 2} .0270986{col 42}{space 1}    1.71{col 51}{space 3}0.087{col 59}{space 4}-.0066954{col 72}{space 3} .0995962
{txt}{space 9}hispanic {c |}{col 19}{res}{space 2} .0361844{col 31}{space 2} .0248984{col 42}{space 1}    1.45{col 51}{space 3}0.146{col 59}{space 4}-.0126463{col 72}{space 3} .0850151
{txt}{space 14}api {c |}{col 19}{res}{space 2}-.0139023{col 31}{space 2} .0236251{col 42}{space 1}   -0.59{col 51}{space 3}0.556{col 59}{space 4}-.0602358{col 72}{space 3} .0324313
{txt}{space 13}WDem {c |}{col 19}{res}{space 2}-.0039737{col 31}{space 2} .0288287{col 42}{space 1}   -0.14{col 51}{space 3}0.890{col 59}{space 4}-.0605127{col 72}{space 3} .0525653
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7864648{col 31}{space 2} .0358586{col 42}{space 1}   21.93{col 51}{space 3}0.000{col 59}{space 4} .7161389{col 72}{space 3} .8567908
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(running {bf:regress} on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 5:1}{txt}{col 51}{lalign 15:Number of obs}{col 66} = {res}{ralign 10:1,918}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 5:1,918}{txt}{col 51}{lalign 15:Population size}{col 66} = {res}{ralign 10:20,913.912}
{txt}{col 51}{lalign 15:Design df}{col 66} = {res}{ralign 10:1,917}
{txt}{col 51}{lalign 15:F({res:8}, {res:1910})}{col 66} = {res}{ralign 10:25.86}
{txt}{col 51}{lalign 15:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 51}{lalign 15:R-squared}{col 66} = {res}{ralign 10:0.1180}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}  Linearized
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0092167{col 31}{space 2} .0217408{col 42}{space 1}    0.42{col 51}{space 3}0.672{col 59}{space 4}-.0334215{col 72}{space 3} .0518548
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1759918{col 31}{space 2} .0290366{col 42}{space 1}   -6.06{col 51}{space 3}0.000{col 59}{space 4}-.2329383{col 72}{space 3}-.1190452
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}  .014672{col 31}{space 2} .0213596{col 42}{space 1}    0.69{col 51}{space 3}0.492{col 59}{space 4}-.0272185{col 72}{space 3} .0565625
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0516579{col 31}{space 2} .0295184{col 42}{space 1}    1.75{col 51}{space 3}0.080{col 59}{space 4}-.0062336{col 72}{space 3} .1095494
{txt}{space 12}black {c |}{col 19}{res}{space 2} .0924838{col 31}{space 2} .0282939{col 42}{space 1}    3.27{col 51}{space 3}0.001{col 59}{space 4} .0369937{col 72}{space 3} .1479739
{txt}{space 9}hispanic {c |}{col 19}{res}{space 2} .0367335{col 31}{space 2}  .027005{col 42}{space 1}    1.36{col 51}{space 3}0.174{col 59}{space 4}-.0162288{col 72}{space 3} .0896957
{txt}{space 14}api {c |}{col 19}{res}{space 2} .0154891{col 31}{space 2} .0256654{col 42}{space 1}    0.60{col 51}{space 3}0.546{col 59}{space 4} -.034846{col 72}{space 3} .0658242
{txt}{space 13}WDem {c |}{col 19}{res}{space 2} .0312084{col 31}{space 2}  .030561{col 42}{space 1}    1.02{col 51}{space 3}0.307{col 59}{space 4}-.0287279{col 72}{space 3} .0911447
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7853123{col 31}{space 2} .0376898{col 42}{space 1}   20.84{col 51}{space 3}0.000{col 59}{space 4}  .711395{col 72}{space 3} .8592295
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(running {bf:regress} on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 5:1}{txt}{col 51}{lalign 15:Number of obs}{col 66} = {res}{ralign 10:1,916}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 5:1,916}{txt}{col 51}{lalign 15:Population size}{col 66} = {res}{ralign 10:20,877.376}
{txt}{col 51}{lalign 15:Design df}{col 66} = {res}{ralign 10:1,915}
{txt}{col 51}{lalign 15:F({res:8}, {res:1908})}{col 66} = {res}{ralign 10:33.02}
{txt}{col 51}{lalign 15:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 51}{lalign 15:R-squared}{col 66} = {res}{ralign 10:0.1593}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}  Linearized
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0175525{col 31}{space 2} .0226086{col 42}{space 1}   -0.78{col 51}{space 3}0.438{col 59}{space 4}-.0618925{col 72}{space 3} .0267876
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.2130158{col 31}{space 2} .0305075{col 42}{space 1}   -6.98{col 51}{space 3}0.000{col 59}{space 4}-.2728472{col 72}{space 3}-.1531844
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0272649{col 31}{space 2} .0220817{col 42}{space 1}    1.23{col 51}{space 3}0.217{col 59}{space 4}-.0160419{col 72}{space 3} .0705716
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0115063{col 31}{space 2} .0297323{col 42}{space 1}    0.39{col 51}{space 3}0.699{col 59}{space 4}-.0468049{col 72}{space 3} .0698175
{txt}{space 12}black {c |}{col 19}{res}{space 2} .0927743{col 31}{space 2} .0295453{col 42}{space 1}    3.14{col 51}{space 3}0.002{col 59}{space 4}   .03483{col 72}{space 3} .1507187
{txt}{space 9}hispanic {c |}{col 19}{res}{space 2} .0434475{col 31}{space 2} .0288765{col 42}{space 1}    1.50{col 51}{space 3}0.133{col 59}{space 4}-.0131852{col 72}{space 3} .1000802
{txt}{space 14}api {c |}{col 19}{res}{space 2}  .011617{col 31}{space 2} .0264849{col 42}{space 1}    0.44{col 51}{space 3}0.661{col 59}{space 4}-.0403253{col 72}{space 3} .0635594
{txt}{space 13}WDem {c |}{col 19}{res}{space 2} .0459396{col 31}{space 2} .0318099{col 42}{space 1}    1.44{col 51}{space 3}0.149{col 59}{space 4}-.0164461{col 72}{space 3} .1083253
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .8156273{col 31}{space 2} .0399779{col 42}{space 1}   20.40{col 51}{space 3}0.000{col 59}{space 4} .7372226{col 72}{space 3}  .894032
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(running {bf:regress} on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 5:1}{txt}{col 51}{lalign 15:Number of obs}{col 66} = {res}{ralign 10:1,918}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 5:1,918}{txt}{col 51}{lalign 15:Population size}{col 66} = {res}{ralign 10:20,913.912}
{txt}{col 51}{lalign 15:Design df}{col 66} = {res}{ralign 10:1,917}
{txt}{col 51}{lalign 15:F({res:8}, {res:1910})}{col 66} = {res}{ralign 10:17.49}
{txt}{col 51}{lalign 15:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 51}{lalign 15:R-squared}{col 66} = {res}{ralign 10:0.0781}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}  Linearized
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0133618{col 31}{space 2} .0210953{col 42}{space 1}   -0.63{col 51}{space 3}0.527{col 59}{space 4}-.0547339{col 72}{space 3} .0280103
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1765271{col 31}{space 2} .0296803{col 42}{space 1}   -5.95{col 51}{space 3}0.000{col 59}{space 4}-.2347361{col 72}{space 3}-.1183181
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}  .009248{col 31}{space 2} .0201844{col 42}{space 1}    0.46{col 51}{space 3}0.647{col 59}{space 4}-.0303378{col 72}{space 3} .0488337
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0041385{col 31}{space 2} .0278903{col 42}{space 1}    0.15{col 51}{space 3}0.882{col 59}{space 4}  -.05056{col 72}{space 3} .0588371
{txt}{space 12}black {c |}{col 19}{res}{space 2} .0240458{col 31}{space 2}  .029466{col 42}{space 1}    0.82{col 51}{space 3}0.415{col 59}{space 4}-.0337429{col 72}{space 3} .0818346
{txt}{space 9}hispanic {c |}{col 19}{res}{space 2} .0081421{col 31}{space 2} .0274503{col 42}{space 1}    0.30{col 51}{space 3}0.767{col 59}{space 4}-.0456935{col 72}{space 3} .0619777
{txt}{space 14}api {c |}{col 19}{res}{space 2}-.0358463{col 31}{space 2} .0248197{col 42}{space 1}   -1.44{col 51}{space 3}0.149{col 59}{space 4}-.0845228{col 72}{space 3} .0128302
{txt}{space 13}WDem {c |}{col 19}{res}{space 2}-.0224697{col 31}{space 2} .0302206{col 42}{space 1}   -0.74{col 51}{space 3}0.457{col 59}{space 4}-.0817385{col 72}{space 3}  .036799
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .8686381{col 31}{space 2} .0371284{col 42}{space 1}   23.40{col 51}{space 3}0.000{col 59}{space 4} .7958219{col 72}{space 3} .9414543
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(running {bf:regress} on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 5:1}{txt}{col 51}{lalign 15:Number of obs}{col 66} = {res}{ralign 10:1,919}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 5:1,919}{txt}{col 51}{lalign 15:Population size}{col 66} = {res}{ralign 10:20,922.958}
{txt}{col 51}{lalign 15:Design df}{col 66} = {res}{ralign 10:1,918}
{txt}{col 51}{lalign 15:F({res:8}, {res:1911})}{col 66} = {res}{ralign 10:7.76}
{txt}{col 51}{lalign 15:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 51}{lalign 15:R-squared}{col 66} = {res}{ralign 10:0.0313}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}  Linearized
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0432885{col 31}{space 2} .0223845{col 42}{space 1}    1.93{col 51}{space 3}0.053{col 59}{space 4}-.0006121{col 72}{space 3} .0871891
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1288173{col 31}{space 2} .0309936{col 42}{space 1}   -4.16{col 51}{space 3}0.000{col 59}{space 4}-.1896019{col 72}{space 3}-.0680326
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0701042{col 31}{space 2} .0224568{col 42}{space 1}   -3.12{col 51}{space 3}0.002{col 59}{space 4}-.1141465{col 72}{space 3}-.0260619
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0944697{col 31}{space 2}  .030763{col 42}{space 1}    3.07{col 51}{space 3}0.002{col 59}{space 4} .0341372{col 72}{space 3} .1548021
{txt}{space 12}black {c |}{col 19}{res}{space 2}-.0110932{col 31}{space 2} .0310961{col 42}{space 1}   -0.36{col 51}{space 3}0.721{col 59}{space 4}-.0720789{col 72}{space 3} .0498925
{txt}{space 9}hispanic {c |}{col 19}{res}{space 2} .0105597{col 31}{space 2} .0286414{col 42}{space 1}    0.37{col 51}{space 3}0.712{col 59}{space 4}-.0456119{col 72}{space 3} .0667312
{txt}{space 14}api {c |}{col 19}{res}{space 2}-.0351421{col 31}{space 2} .0268043{col 42}{space 1}   -1.31{col 51}{space 3}0.190{col 59}{space 4}-.0877107{col 72}{space 3} .0174265
{txt}{space 13}WDem {c |}{col 19}{res}{space 2}-.0636017{col 31}{space 2} .0321872{col 42}{space 1}   -1.98{col 51}{space 3}0.048{col 59}{space 4}-.1267274{col 72}{space 3}-.0004761
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .8132465{col 31}{space 2} .0402597{col 42}{space 1}   20.20{col 51}{space 3}0.000{col 59}{space 4} .7342892{col 72}{space 3} .8922039
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. coefplot covid_gene_wt covid_flout_protocols_wt covid_neighborhood_wt covid_jobs_wt covid_healthcare_wt covid_preexisting_wt, keep(race_bio_identity) xline(0, lcolor(red) lpattern(dash) ) ///
> legend(position(3) row(6) region(margin(r+5))) coeflabels(race_bio_identity=" ", noticks) ///
> plotlabels(`" " ""Genetic Differences"" ""' `" " ""Flout Protocols"" " "' `" " ""Neighborhood Hot Spots"" " "'  `" " ""Occupational Hazards"" " "' `" " ""Healthcare Access"" " "' `" " ""Preexisting Conditions"" ""' ) ///
> title("DVs: Explanations for COVID-19 Racial Disparities" "OLS Coefficient on Defining Race as Biology", size(medium)) xsize(10) ysize(7)
{res}{txt}
{com}. graph export Figure4.pdf, replace
{txt}{p 0 4 2}
file {bf}
Figure4.pdf{rm}
saved as
PDF
format
{p_end}

{com}. **********END FIGURE 4**********
. 
. **********FOR APPENDIX**********
. est table covid_gene_wt covid_preexisting_wt covid_jobs_wt covid_healthcare_wt covid_neighborhood_wt covid_flout_protocols_wt , b(%9.2f) se style(col) eq(1) stats(N) modelwidth(1)
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 9:covid_g~t} {c |} {center 9:covid_p~t} {c |} {center 9:covid_j~t} {c |} {center 9:covid_h~t} {c |} {center 9:covid_n~t} {c |} {center 9:covid_f~t} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.10}{txt} {c |}{res} {ralign 9:0.00}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:-0.02}{txt} {c |}{res} {ralign 9:-0.01}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.16}{txt} {c |}{res} {ralign 9:-0.08}{txt} {c |}{res} {ralign 9:-0.18}{txt} {c |}{res} {ralign 9:-0.21}{txt} {c |}{res} {ralign 9:-0.18}{txt} {c |}{res} {ralign 9:-0.13}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.08}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:-0.07}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.03}{txt} {c |}{res} {ralign 9:0.09}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:0.00}{txt} {c |}{res} {ralign 9:0.09}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}
{res}{txt}{c |} {space 7}black {c |}{res} {ralign 9:-0.02}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.09}{txt} {c |}{res} {ralign 9:0.09}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:-0.01}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}
{res}{txt}{c |} {space 4}hispanic {c |}{res} {ralign 9:-0.03}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}
{res}{txt}{c |} {space 9}api {c |}{res} {ralign 9:-0.10}{txt} {c |}{res} {ralign 9:-0.01}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}
{res}{txt}{c |} {space 8}WDem {c |}{res} {ralign 9:-0.09}{txt} {c |}{res} {ralign 9:-0.00}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:-0.02}{txt} {c |}{res} {ralign 9:-0.06}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.76}{txt} {c |}{res} {ralign 9:0.79}{txt} {c |}{res} {ralign 9:0.79}{txt} {c |}{res} {ralign 9:0.82}{txt} {c |}{res} {ralign 9:0.87}{txt} {c |}{res} {ralign 9:0.81}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:1917}{txt} {c |}{res} {ralign 9:1918}{txt} {c |}{res} {ralign 9:1918}{txt} {c |}{res} {ralign 9:1916}{txt} {c |}{res} {ralign 9:1918}{txt} {c |}{res} {ralign 9:1919}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BRC}
{ralign 88:Legend: b/se}
{res}{txt}
{com}. est table covid_gene_wt covid_preexisting_wt covid_jobs_wt covid_healthcare_wt covid_neighborhood_wt covid_flout_protocols_wt , b(%9.2f) star(.05 .01 .001) style(col) eq(1) stats(N)
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 12:covid_gene~t} {c |} {center 12:covid_pree~t} {c |} {center 12:covid_jobs~t} {c |} {center 12:covid_heal~t} {c |} {center 12:covid_neig~t} {c |} {center 12:covid_flou~t} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.10}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.16}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.08}{lalign 3:**}{txt} {c |}{res} {ralign 9:-0.18}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.21}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.18}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.13}{lalign 3:***}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.08}{lalign 3:**}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.07}{lalign 3:**}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.09}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:0.09}{lalign 3:**}{txt} {c |}
{res}{txt}{c |} {space 7}black {c |}{res} {ralign 9:-0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:0.09}{lalign 3:**}{txt} {c |}{res} {ralign 9:0.09}{lalign 3:**}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.01}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 4}hispanic {c |}{res} {ralign 9:-0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 9}api {c |}{res} {ralign 9:-0.10}{lalign 3:**}{txt} {c |}{res} {ralign 9:-0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 8}WDem {c |}{res} {ralign 9:-0.09}{lalign 3:*}{txt} {c |}{res} {ralign 9:-0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.06}{lalign 3:*}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.76}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.79}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.79}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.82}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.87}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.81}{lalign 3:***}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:1917}{lalign 3:}{txt} {c |}{res} {ralign 9:1918}{lalign 3:}{txt} {c |}{res} {ralign 9:1918}{lalign 3:}{txt} {c |}{res} {ralign 9:1916}{lalign 3:}{txt} {c |}{res} {ralign 9:1918}{lalign 3:}{txt} {c |}{res} {ralign 9:1919}{lalign 3:}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BRC}
{ralign 106:Legend: * p<.05; ** p<.01; *** p<.001}
{res}{txt}
{com}. 
. //New model separately by five groups
. forval j=1/5 {c -(}
{txt}  2{com}.         foreach v of varlist covid_gene covid_preexisting covid_jobs covid_healthcare covid_neighborhood covid_flout_protocols {c -(}
{txt}  3{com}.         reg `v' race_bio_identity pid7cata ed6cat age01 black hispanic api if fivegroups==`j' & ref_covid_battery~=6
{txt}  4{com}. est store `v'_`j'
{txt}  5{com}.         {c )-}
{txt}  6{com}.         {c )-}
{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     1.45
{txt}       Model {c |} {res} .579246558         4   .14481164   {txt}Prob > F        ={res}    0.2167
{txt}    Residual {c |} {res} 36.5315635       366  .099813015   {txt}R-squared       ={res}    0.0156
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0049
{txt}       Total {c |} {res}   37.11081       370  .100299487   {txt}Root MSE        =   {res} .31593

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0324745{col 31}{space 2} .0568972{col 42}{space 1}    0.57{col 51}{space 3}0.569{col 59}{space 4} -.079412{col 72}{space 3}  .144361
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0591964{col 31}{space 2} .0527821{col 42}{space 1}    1.12{col 51}{space 3}0.263{col 59}{space 4}-.0445978{col 72}{space 3} .1629905
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0742419{col 31}{space 2} .0588599{col 42}{space 1}    1.26{col 51}{space 3}0.208{col 59}{space 4}-.0415041{col 72}{space 3} .1899879
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.1568964{col 31}{space 2} .0781705{col 42}{space 1}   -2.01{col 51}{space 3}0.045{col 59}{space 4}-.3106161{col 72}{space 3}-.0031768
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .5631289{col 31}{space 2} .0609746{col 42}{space 1}    9.24{col 51}{space 3}0.000{col 59}{space 4} .4432244{col 72}{space 3} .6830334
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     3.60
{txt}       Model {c |} {res}  .81048245         4  .202620613   {txt}Prob > F        ={res}    0.0068
{txt}    Residual {c |} {res} 20.6139349       366  .056322226   {txt}R-squared       ={res}    0.0378
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0273
{txt}       Total {c |} {res} 21.4244173       370  .057903831   {txt}Root MSE        =   {res} .23732

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0398849{col 31}{space 2} .0427403{col 42}{space 1}   -0.93{col 51}{space 3}0.351{col 59}{space 4}-.1239322{col 72}{space 3} .0441624
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0054818{col 31}{space 2}  .039649{col 42}{space 1}   -0.14{col 51}{space 3}0.890{col 59}{space 4}-.0834503{col 72}{space 3} .0724867
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .1194409{col 31}{space 2} .0442146{col 42}{space 1}    2.70{col 51}{space 3}0.007{col 59}{space 4} .0324944{col 72}{space 3} .2063875
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1065469{col 31}{space 2} .0587204{col 42}{space 1}    1.81{col 51}{space 3}0.070{col 59}{space 4}-.0089248{col 72}{space 3} .2220186
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7016881{col 31}{space 2} .0458031{col 42}{space 1}   15.32{col 51}{space 3}0.000{col 59}{space 4} .6116178{col 72}{space 3} .7917585
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     5.93
{txt}       Model {c |} {res} 1.67427775         4  .418569437   {txt}Prob > F        ={res}    0.0001
{txt}    Residual {c |} {res} 25.8509623       366  .070631045   {txt}R-squared       ={res}    0.0608
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0506
{txt}       Total {c |} {res} 27.5252401       370  .074392541   {txt}Root MSE        =   {res} .26577

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0009218{col 31}{space 2} .0478625{col 42}{space 1}   -0.02{col 51}{space 3}0.985{col 59}{space 4}-.0950418{col 72}{space 3} .0931982
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1862137{col 31}{space 2} .0444008{col 42}{space 1}   -4.19{col 51}{space 3}0.000{col 59}{space 4}-.2735264{col 72}{space 3}-.0989011
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0851424{col 31}{space 2} .0495135{col 42}{space 1}    1.72{col 51}{space 3}0.086{col 59}{space 4}-.0122242{col 72}{space 3} .1825091
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0157478{col 31}{space 2} .0657578{col 42}{space 1}   -0.24{col 51}{space 3}0.811{col 59}{space 4}-.1450582{col 72}{space 3} .1135627
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2}  .785093{col 31}{space 2} .0512924{col 42}{space 1}   15.31{col 51}{space 3}0.000{col 59}{space 4} .6842281{col 72}{space 3} .8859578
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     7.39
{txt}       Model {c |} {res} 2.04979012         4  .512447531   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 25.3731616       366  .069325578   {txt}R-squared       ={res}    0.0747
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0646
{txt}       Total {c |} {res} 27.4229517       370  .074116086   {txt}Root MSE        =   {res}  .2633

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0325693{col 31}{space 2} .0474181{col 42}{space 1}   -0.69{col 51}{space 3}0.493{col 59}{space 4}-.1258154{col 72}{space 3} .0606768
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} -.229716{col 31}{space 2} .0439885{col 42}{space 1}   -5.22{col 51}{space 3}0.000{col 59}{space 4} -.316218{col 72}{space 3} -.143214
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0089697{col 31}{space 2} .0490538{col 42}{space 1}    0.18{col 51}{space 3}0.855{col 59}{space 4} -.087493{col 72}{space 3} .1054323
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0278694{col 31}{space 2} .0651472{col 42}{space 1}   -0.43{col 51}{space 3}0.669{col 59}{space 4}-.1559792{col 72}{space 3} .1002405
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8691811{col 31}{space 2} .0508162{col 42}{space 1}   17.10{col 51}{space 3}0.000{col 59}{space 4} .7692527{col 72}{space 3} .9691094
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     1.62
{txt}       Model {c |} {res}  .39584855         4  .098962138   {txt}Prob > F        ={res}    0.1673
{txt}    Residual {c |} {res}  22.289605       366   .06090056   {txt}R-squared       ={res}    0.0174
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0067
{txt}       Total {c |} {res} 22.6854535       370  .061312037   {txt}Root MSE        =   {res} .24678

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0167589{col 31}{space 2} .0444435{col 42}{space 1}    0.38{col 51}{space 3}0.706{col 59}{space 4}-.0706377{col 72}{space 3} .1041556
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0870414{col 31}{space 2} .0412291{col 42}{space 1}   -2.11{col 51}{space 3}0.035{col 59}{space 4} -.168117{col 72}{space 3}-.0059658
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0454811{col 31}{space 2} .0459766{col 42}{space 1}    0.99{col 51}{space 3}0.323{col 59}{space 4}-.0449302{col 72}{space 3} .1358925
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0149529{col 31}{space 2} .0610604{col 42}{space 1}   -0.24{col 51}{space 3}0.807{col 59}{space 4}-.1350262{col 72}{space 3} .1051204
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7603401{col 31}{space 2} .0476284{col 42}{space 1}   15.96{col 51}{space 3}0.000{col 59}{space 4} .6666804{col 72}{space 3} .8539997
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     0.73
{txt}       Model {c |} {res} .234894137         4  .058723534   {txt}Prob > F        ={res}    0.5689
{txt}    Residual {c |} {res} 29.2611228       366  .079948423   {txt}R-squared       ={res}    0.0080
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0029
{txt}       Total {c |} {res} 29.4960169       370  .079718965   {txt}Root MSE        =   {res} .28275

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0684512{col 31}{space 2} .0509216{col 42}{space 1}    1.34{col 51}{space 3}0.180{col 59}{space 4}-.0316845{col 72}{space 3} .1685869
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0430464{col 31}{space 2} .0472387{col 42}{space 1}   -0.91{col 51}{space 3}0.363{col 59}{space 4}-.1359397{col 72}{space 3} .0498468
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} -.033915{col 31}{space 2} .0526782{col 42}{space 1}   -0.64{col 51}{space 3}0.520{col 59}{space 4}-.1375049{col 72}{space 3} .0696749
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0434023{col 31}{space 2} .0699607{col 42}{space 1}    0.62{col 51}{space 3}0.535{col 59}{space 4}-.0941731{col 72}{space 3} .1809777
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7210282{col 31}{space 2} .0545708{col 42}{space 1}   13.21{col 51}{space 3}0.000{col 59}{space 4} .6137166{col 72}{space 3} .8283399
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     8.73
{txt}       Model {c |} {res} 3.71725623         4  .929314057   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 39.9013221       375  .106403526   {txt}R-squared       ={res}    0.0852
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0755
{txt}       Total {c |} {res} 43.6185783       379  .115088597   {txt}Root MSE        =   {res}  .3262

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .1058281{col 31}{space 2} .0510399{col 42}{space 1}    2.07{col 51}{space 3}0.039{col 59}{space 4} .0054678{col 72}{space 3} .2061884
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.3057266{col 31}{space 2} .0621366{col 42}{space 1}   -4.92{col 51}{space 3}0.000{col 59}{space 4}-.4279064{col 72}{space 3}-.1835468
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0999222{col 31}{space 2} .0585648{col 42}{space 1}   -1.71{col 51}{space 3}0.089{col 59}{space 4}-.2150788{col 72}{space 3} .0152345
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0823343{col 31}{space 2} .0738895{col 42}{space 1}   -1.11{col 51}{space 3}0.266{col 59}{space 4} -.227624{col 72}{space 3} .0629555
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7988455{col 31}{space 2} .0514093{col 42}{space 1}   15.54{col 51}{space 3}0.000{col 59}{space 4} .6977589{col 72}{space 3} .8999321
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     4.60
{txt}       Model {c |} {res} .953243977         4  .238310994   {txt}Prob > F        ={res}    0.0012
{txt}    Residual {c |} {res} 19.4162107       375  .051776562   {txt}R-squared       ={res}    0.0468
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0366
{txt}       Total {c |} {res} 20.3694547       379  .053745263   {txt}Root MSE        =   {res} .22754

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0313973{col 31}{space 2}  .035604{col 42}{space 1}    0.88{col 51}{space 3}0.378{col 59}{space 4}-.0386111{col 72}{space 3} .1014058
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1227863{col 31}{space 2} .0433447{col 42}{space 1}   -2.83{col 51}{space 3}0.005{col 59}{space 4}-.2080154{col 72}{space 3}-.0375572
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0112409{col 31}{space 2} .0408532{col 42}{space 1}    0.28{col 51}{space 3}0.783{col 59}{space 4}-.0690891{col 72}{space 3} .0915709
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .128478{col 31}{space 2} .0515432{col 42}{space 1}    2.49{col 51}{space 3}0.013{col 59}{space 4}  .027128{col 72}{space 3} .2298279
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8195459{col 31}{space 2} .0358617{col 42}{space 1}   22.85{col 51}{space 3}0.000{col 59}{space 4} .7490308{col 72}{space 3}  .890061
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     8.43
{txt}       Model {c |} {res} 1.44288195         4  .360720487   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 16.0441898       375  .042784506   {txt}R-squared       ={res}    0.0825
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0727
{txt}       Total {c |} {res} 17.4870717       379  .046140031   {txt}Root MSE        =   {res} .20684

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0877688{col 31}{space 2}  .032365{col 42}{space 1}    2.71{col 51}{space 3}0.007{col 59}{space 4} .0241292{col 72}{space 3} .1514083
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1531162{col 31}{space 2} .0394015{col 42}{space 1}   -3.89{col 51}{space 3}0.000{col 59}{space 4}-.2305918{col 72}{space 3}-.0756407
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0199343{col 31}{space 2} .0371366{col 42}{space 1}    0.54{col 51}{space 3}0.592{col 59}{space 4}-.0530878{col 72}{space 3} .0929563
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1145094{col 31}{space 2} .0468542{col 42}{space 1}    2.44{col 51}{space 3}0.015{col 59}{space 4} .0223796{col 72}{space 3} .2066392
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8019836{col 31}{space 2} .0325992{col 42}{space 1}   24.60{col 51}{space 3}0.000{col 59}{space 4} .7378835{col 72}{space 3} .8660838
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       379
{txt}{hline 13}{c +}{hline 34}   F(4, 374)       = {res}     6.98
{txt}       Model {c |} {res} 1.40336645         4  .350841612   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.7894744       374  .050239236   {txt}R-squared       ={res}    0.0695
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0595
{txt}       Total {c |} {res} 20.1928408       378  .053420214   {txt}Root MSE        =   {res} .22414

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0318773{col 31}{space 2} .0351275{col 42}{space 1}    0.91{col 51}{space 3}0.365{col 59}{space 4}-.0371948{col 72}{space 3} .1009495
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1167946{col 31}{space 2} .0427444{col 42}{space 1}   -2.73{col 51}{space 3}0.007{col 59}{space 4}-.2008441{col 72}{space 3}-.0327451
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0719376{col 31}{space 2} .0402421{col 42}{space 1}    1.79{col 51}{space 3}0.075{col 59}{space 4}-.0071916{col 72}{space 3} .1510667
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1609723{col 31}{space 2}  .050811{col 42}{space 1}    3.17{col 51}{space 3}0.002{col 59}{space 4} .0610613{col 72}{space 3} .2608834
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7835973{col 31}{space 2} .0354449{col 42}{space 1}   22.11{col 51}{space 3}0.000{col 59}{space 4} .7139011{col 72}{space 3} .8532935
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}    10.04
{txt}       Model {c |} {res} 2.03008062         4  .507520156   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.9610267       375  .050562738   {txt}R-squared       ={res}    0.0967
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0871
{txt}       Total {c |} {res} 20.9911073       379  .055385507   {txt}Root MSE        =   {res} .22486

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0517345{col 31}{space 2} .0351842{col 42}{space 1}    1.47{col 51}{space 3}0.142{col 59}{space 4}-.0174484{col 72}{space 3} .1209175
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.2347881{col 31}{space 2} .0428336{col 42}{space 1}   -5.48{col 51}{space 3}0.000{col 59}{space 4}-.3190123{col 72}{space 3} -.150564
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0607888{col 31}{space 2} .0403714{col 42}{space 1}    1.51{col 51}{space 3}0.133{col 59}{space 4} -.018594{col 72}{space 3} .1401715
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0594472{col 31}{space 2} .0509355{col 42}{space 1}    1.17{col 51}{space 3}0.244{col 59}{space 4}-.0407077{col 72}{space 3} .1596022
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8220856{col 31}{space 2} .0354388{col 42}{space 1}   23.20{col 51}{space 3}0.000{col 59}{space 4} .7524019{col 72}{space 3} .8917692
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     8.95
{txt}       Model {c |} {res} 2.64789078         4  .661972695   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 27.7336231       375  .073956328   {txt}R-squared       ={res}    0.0872
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0774
{txt}       Total {c |} {res} 30.3815139       379  .080162306   {txt}Root MSE        =   {res} .27195

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .1361745{col 31}{space 2}  .042552{col 42}{space 1}    3.20{col 51}{space 3}0.001{col 59}{space 4} .0525042{col 72}{space 3} .2198449
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.2100863{col 31}{space 2} .0518033{col 42}{space 1}   -4.06{col 51}{space 3}0.000{col 59}{space 4}-.3119475{col 72}{space 3} -.108225
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0753691{col 31}{space 2} .0488255{col 42}{space 1}   -1.54{col 51}{space 3}0.124{col 59}{space 4}-.1713752{col 72}{space 3}  .020637
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1183134{col 31}{space 2} .0616017{col 42}{space 1}    1.92{col 51}{space 3}0.056{col 59}{space 4}-.0028146{col 72}{space 3} .2394415
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7589043{col 31}{space 2} .0428599{col 42}{space 1}   17.71{col 51}{space 3}0.000{col 59}{space 4} .6746284{col 72}{space 3} .8431801
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       360
{txt}{hline 13}{c +}{hline 34}   F(4, 355)       = {res}     4.07
{txt}       Model {c |} {res} 1.64947521         4  .412368804   {txt}Prob > F        ={res}    0.0031
{txt}    Residual {c |} {res} 35.9907439       355  .101382377   {txt}R-squared       ={res}    0.0438
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0330
{txt}       Total {c |} {res} 37.6402192       359  .104847407   {txt}Root MSE        =   {res} .31841

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0533694{col 31}{space 2} .0519445{col 42}{space 1}    1.03{col 51}{space 3}0.305{col 59}{space 4}-.0487882{col 72}{space 3} .1555271
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1659894{col 31}{space 2} .0508141{col 42}{space 1}   -3.27{col 51}{space 3}0.001{col 59}{space 4}-.2659238{col 72}{space 3} -.066055
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1071097{col 31}{space 2} .0595468{col 42}{space 1}   -1.80{col 51}{space 3}0.073{col 59}{space 4}-.2242185{col 72}{space 3} .0099992
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0473796{col 31}{space 2} .0787381{col 42}{space 1}   -0.60{col 51}{space 3}0.548{col 59}{space 4}-.2022314{col 72}{space 3} .1074722
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7841609{col 31}{space 2} .0524649{col 42}{space 1}   14.95{col 51}{space 3}0.000{col 59}{space 4} .6809797{col 72}{space 3} .8873421
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       361
{txt}{hline 13}{c +}{hline 34}   F(4, 356)       = {res}     3.23
{txt}       Model {c |} {res} .653859767         4  .163464942   {txt}Prob > F        ={res}    0.0126
{txt}    Residual {c |} {res} 17.9907714       356  .050535875   {txt}R-squared       ={res}    0.0351
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0242
{txt}       Total {c |} {res} 18.6446312       360  .051790642   {txt}Root MSE        =   {res}  .2248

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0029366{col 31}{space 2} .0366683{col 42}{space 1}   -0.08{col 51}{space 3}0.936{col 59}{space 4}-.0750503{col 72}{space 3}  .069177
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0704206{col 31}{space 2} .0358637{col 42}{space 1}   -1.96{col 51}{space 3}0.050{col 59}{space 4} -.140952{col 72}{space 3} .0001108
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0678801{col 31}{space 2} .0420408{col 42}{space 1}    1.61{col 51}{space 3}0.107{col 59}{space 4}-.0147994{col 72}{space 3} .1505597
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1217662{col 31}{space 2} .0555895{col 42}{space 1}    2.19{col 51}{space 3}0.029{col 59}{space 4} .0124411{col 72}{space 3} .2310912
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7953463{col 31}{space 2} .0370303{col 42}{space 1}   21.48{col 51}{space 3}0.000{col 59}{space 4} .7225206{col 72}{space 3}  .868172
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       360
{txt}{hline 13}{c +}{hline 34}   F(4, 355)       = {res}     5.46
{txt}       Model {c |} {res} 1.54359277         4  .385898192   {txt}Prob > F        ={res}    0.0003
{txt}    Residual {c |} {res} 25.0849664       355  .070661877   {txt}R-squared       ={res}    0.0580
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0474
{txt}       Total {c |} {res} 26.6285591       359  .074174259   {txt}Root MSE        =   {res} .26582

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0197356{col 31}{space 2} .0433662{col 42}{space 1}   -0.46{col 51}{space 3}0.649{col 59}{space 4}-.1050225{col 72}{space 3} .0655512
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1817085{col 31}{space 2} .0424224{col 42}{space 1}   -4.28{col 51}{space 3}0.000{col 59}{space 4}-.2651393{col 72}{space 3}-.0982777
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0333824{col 31}{space 2}  .049713{col 42}{space 1}    0.67{col 51}{space 3}0.502{col 59}{space 4}-.0643865{col 72}{space 3} .1311514
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1028598{col 31}{space 2}  .065735{col 42}{space 1}    1.56{col 51}{space 3}0.119{col 59}{space 4}-.0264191{col 72}{space 3} .2321387
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8173275{col 31}{space 2} .0438006{col 42}{space 1}   18.66{col 51}{space 3}0.000{col 59}{space 4} .7311862{col 72}{space 3} .9034689
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       361
{txt}{hline 13}{c +}{hline 34}   F(4, 356)       = {res}    11.92
{txt}       Model {c |} {res}  3.1784622         4   .79461555   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 23.7387248       356  .066681811   {txt}R-squared       ={res}    0.1181
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1082
{txt}       Total {c |} {res}  26.917187       360  .074769964   {txt}Root MSE        =   {res} .25823

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0067312{col 31}{space 2} .0421206{col 42}{space 1}    0.16{col 51}{space 3}0.873{col 59}{space 4}-.0761052{col 72}{space 3} .0895676
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.2833748{col 31}{space 2} .0411964{col 42}{space 1}   -6.88{col 51}{space 3}0.000{col 59}{space 4}-.3643937{col 72}{space 3}-.2023558
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0040141{col 31}{space 2}  .048292{col 42}{space 1}   -0.08{col 51}{space 3}0.934{col 59}{space 4}-.0989875{col 72}{space 3} .0909592
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .066689{col 31}{space 2} .0638552{col 42}{space 1}    1.04{col 51}{space 3}0.297{col 59}{space 4}-.0588919{col 72}{space 3} .1922699
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8653796{col 31}{space 2} .0425365{col 42}{space 1}   20.34{col 51}{space 3}0.000{col 59}{space 4} .7817253{col 72}{space 3} .9490339
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       360
{txt}{hline 13}{c +}{hline 34}   F(4, 355)       = {res}     5.53
{txt}       Model {c |} {res} 1.41011266         4  .352528166   {txt}Prob > F        ={res}    0.0002
{txt}    Residual {c |} {res} 22.6211965       355   .06372168   {txt}R-squared       ={res}    0.0587
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0481
{txt}       Total {c |} {res} 24.0313092       359   .06693958   {txt}Root MSE        =   {res} .25243

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0356082{col 31}{space 2} .0411815{col 42}{space 1}   -0.86{col 51}{space 3}0.388{col 59}{space 4}-.1165985{col 72}{space 3} .0453822
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1820329{col 31}{space 2} .0402853{col 42}{space 1}   -4.52{col 51}{space 3}0.000{col 59}{space 4}-.2612607{col 72}{space 3}-.1028051
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0073862{col 31}{space 2} .0472086{col 42}{space 1}   -0.16{col 51}{space 3}0.876{col 59}{space 4}-.1002298{col 72}{space 3} .0854574
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0604398{col 31}{space 2} .0624234{col 42}{space 1}    0.97{col 51}{space 3}0.334{col 59}{space 4}-.0623263{col 72}{space 3}  .183206
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8818313{col 31}{space 2} .0415941{col 42}{space 1}   21.20{col 51}{space 3}0.000{col 59}{space 4} .8000295{col 72}{space 3} .9636331
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       361
{txt}{hline 13}{c +}{hline 34}   F(4, 356)       = {res}     2.19
{txt}       Model {c |} {res}  .67025829         4  .167564573   {txt}Prob > F        ={res}    0.0699
{txt}    Residual {c |} {res} 27.2619763       356  .076578585   {txt}R-squared       ={res}    0.0240
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0130
{txt}       Total {c |} {res} 27.9322346       360  .077589541   {txt}Root MSE        =   {res} .27673

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0229041{col 31}{space 2} .0451382{col 42}{space 1}    0.51{col 51}{space 3}0.612{col 59}{space 4}-.0658669{col 72}{space 3} .1116751
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1194934{col 31}{space 2} .0441478{col 42}{space 1}   -2.71{col 51}{space 3}0.007{col 59}{space 4}-.2063168{col 72}{space 3}-.0326701
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0140755{col 31}{space 2} .0517517{col 42}{space 1}   -0.27{col 51}{space 3}0.786{col 59}{space 4} -.115853{col 72}{space 3} .0877021
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1014652{col 31}{space 2}   .06843{col 42}{space 1}    1.48{col 51}{space 3}0.139{col 59}{space 4}-.0331126{col 72}{space 3} .2360431
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8061818{col 31}{space 2} .0455839{col 42}{space 1}   17.69{col 51}{space 3}0.000{col 59}{space 4} .7165342{col 72}{space 3} .8958293
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     7.42
{txt}       Model {c |} {res} 2.98877648         4   .74719412   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  40.467252       402  .100664806   {txt}R-squared       ={res}    0.0688
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0595
{txt}       Total {c |} {res} 43.4560284       406  .107034553   {txt}Root MSE        =   {res} .31728

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .2133851{col 31}{space 2} .0515421{col 42}{space 1}    4.14{col 51}{space 3}0.000{col 59}{space 4} .1120593{col 72}{space 3} .3147108
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0846483{col 31}{space 2} .1596313{col 42}{space 1}    0.53{col 51}{space 3}0.596{col 59}{space 4}-.2291681{col 72}{space 3} .3984647
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1760361{col 31}{space 2} .0467479{col 42}{space 1}   -3.77{col 51}{space 3}0.000{col 59}{space 4}-.2679369{col 72}{space 3}-.0841352
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .002533{col 31}{space 2} .0659922{col 42}{space 1}    0.04{col 51}{space 3}0.969{col 59}{space 4}-.1271999{col 72}{space 3}  .132266
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6271268{col 31}{space 2} .0567527{col 42}{space 1}   11.05{col 51}{space 3}0.000{col 59}{space 4} .5155576{col 72}{space 3}  .738696
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     2.28
{txt}       Model {c |} {res} .412443651         4  .103110913   {txt}Prob > F        ={res}    0.0597
{txt}    Residual {c |} {res} 18.1452058       402  .045137328   {txt}R-squared       ={res}    0.0222
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0125
{txt}       Total {c |} {res} 18.5576495       406  .045708496   {txt}Root MSE        =   {res} .21246

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0573509{col 31}{space 2} .0345137{col 42}{space 1}    1.66{col 51}{space 3}0.097{col 59}{space 4} -.010499{col 72}{space 3} .1252007
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1970412{col 31}{space 2} .1068925{col 42}{space 1}   -1.84{col 51}{space 3}0.066{col 59}{space 4}-.4071793{col 72}{space 3} .0130968
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0019346{col 31}{space 2} .0313034{col 42}{space 1}   -0.06{col 51}{space 3}0.951{col 59}{space 4}-.0634734{col 72}{space 3} .0596041
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0722703{col 31}{space 2} .0441898{col 42}{space 1}    1.64{col 51}{space 3}0.103{col 59}{space 4}-.0146016{col 72}{space 3} .1591422
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7817348{col 31}{space 2} .0380028{col 42}{space 1}   20.57{col 51}{space 3}0.000{col 59}{space 4} .7070258{col 72}{space 3} .8564439
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     2.00
{txt}       Model {c |} {res} .404118445         4  .101029611   {txt}Prob > F        ={res}    0.0944
{txt}    Residual {c |} {res} 20.3488663       402   .05061907   {txt}R-squared       ={res}    0.0195
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0097
{txt}       Total {c |} {res} 20.7529847       406  .051115726   {txt}Root MSE        =   {res} .22499

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0547933{col 31}{space 2} .0365494{col 42}{space 1}    1.50{col 51}{space 3}0.135{col 59}{space 4}-.0170586{col 72}{space 3} .1266452
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} -.182361{col 31}{space 2} .1131974{col 42}{space 1}   -1.61{col 51}{space 3}0.108{col 59}{space 4}-.4048938{col 72}{space 3} .0401717
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0407347{col 31}{space 2} .0331497{col 42}{space 1}    1.23{col 51}{space 3}0.220{col 59}{space 4}-.0244338{col 72}{space 3} .1059032
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0324152{col 31}{space 2} .0467962{col 42}{space 1}    0.69{col 51}{space 3}0.489{col 59}{space 4}-.0595807{col 72}{space 3} .1244111
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7821882{col 31}{space 2} .0402444{col 42}{space 1}   19.44{col 51}{space 3}0.000{col 59}{space 4} .7030725{col 72}{space 3} .8613038
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     1.12
{txt}       Model {c |} {res} .217652612         4  .054413153   {txt}Prob > F        ={res}    0.3462
{txt}    Residual {c |} {res} 19.5187075       402  .048553999   {txt}R-squared       ={res}    0.0110
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0012
{txt}       Total {c |} {res} 19.7363601       406  .048611724   {txt}Root MSE        =   {res} .22035

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0252626{col 31}{space 2} .0357961{col 42}{space 1}    0.71{col 51}{space 3}0.481{col 59}{space 4}-.0451084{col 72}{space 3} .0956335
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1203537{col 31}{space 2} .1108643{col 42}{space 1}   -1.09{col 51}{space 3}0.278{col 59}{space 4}-.3382999{col 72}{space 3} .0975925
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}   .04375{col 31}{space 2} .0324665{col 42}{space 1}    1.35{col 51}{space 3}0.179{col 59}{space 4}-.0200753{col 72}{space 3} .1075754
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0241993{col 31}{space 2} .0458317{col 42}{space 1}    0.53{col 51}{space 3}0.598{col 59}{space 4}-.0659006{col 72}{space 3} .1142991
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8130975{col 31}{space 2} .0394149{col 42}{space 1}   20.63{col 51}{space 3}0.000{col 59}{space 4} .7356124{col 72}{space 3} .8905826
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     0.84
{txt}       Model {c |} {res} .156200442         4  .039050111   {txt}Prob > F        ={res}    0.4986
{txt}    Residual {c |} {res} 18.6263734       402  .046334262   {txt}R-squared       ={res}    0.0083
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0016
{txt}       Total {c |} {res} 18.7825738       406  .046262497   {txt}Root MSE        =   {res} .21525

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0210827{col 31}{space 2} .0349683{col 42}{space 1}    0.60{col 51}{space 3}0.547{col 59}{space 4}-.0476609{col 72}{space 3} .0898262
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1740544{col 31}{space 2} .1083005{col 42}{space 1}   -1.61{col 51}{space 3}0.109{col 59}{space 4}-.3869605{col 72}{space 3} .0388516
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0065647{col 31}{space 2} .0317157{col 42}{space 1}    0.21{col 51}{space 3}0.836{col 59}{space 4}-.0557847{col 72}{space 3}  .068914
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0175605{col 31}{space 2} .0447718{col 42}{space 1}   -0.39{col 51}{space 3}0.695{col 59}{space 4}-.1055767{col 72}{space 3} .0704557
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8352892{col 31}{space 2} .0385034{col 42}{space 1}   21.69{col 51}{space 3}0.000{col 59}{space 4} .7595961{col 72}{space 3} .9109824
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     4.09
{txt}       Model {c |} {res} 1.12909941         4  .282274851   {txt}Prob > F        ={res}    0.0029
{txt}    Residual {c |} {res} 27.7268853       402  .068972351   {txt}R-squared       ={res}    0.0391
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0296
{txt}       Total {c |} {res} 28.8559847       406  .071073854   {txt}Root MSE        =   {res} .26263

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .1066946{col 31}{space 2} .0426639{col 42}{space 1}    2.50{col 51}{space 3}0.013{col 59}{space 4} .0228223{col 72}{space 3} .1905669
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0273028{col 31}{space 2} .1321347{col 42}{space 1}    0.21{col 51}{space 3}0.836{col 59}{space 4}-.2324584{col 72}{space 3}  .287064
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1284749{col 31}{space 2} .0386955{col 42}{space 1}   -3.32{col 51}{space 3}0.001{col 59}{space 4}-.2045458{col 72}{space 3}-.0524041
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0097445{col 31}{space 2}  .054625{col 42}{space 1}    0.18{col 51}{space 3}0.859{col 59}{space 4}-.0976418{col 72}{space 3} .1171308
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7685589{col 31}{space 2}  .046977{col 42}{space 1}   16.36{col 51}{space 3}0.000{col 59}{space 4} .6762076{col 72}{space 3} .8609102
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       399
{txt}{hline 13}{c +}{hline 34}   F(4, 394)       = {res}     0.45
{txt}       Model {c |} {res}  .16765988         4   .04191497   {txt}Prob > F        ={res}    0.7713
{txt}    Residual {c |} {res} 36.5800093       394  .092842663   {txt}R-squared       ={res}    0.0046
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0055
{txt}       Total {c |} {res} 36.7476692       398  .092330827   {txt}Root MSE        =   {res}  .3047

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0202144{col 31}{space 2} .0471224{col 42}{space 1}    0.43{col 51}{space 3}0.668{col 59}{space 4}-.0724284{col 72}{space 3} .1128572
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0433427{col 31}{space 2} .1512175{col 42}{space 1}   -0.29{col 51}{space 3}0.775{col 59}{space 4}-.3406367{col 72}{space 3} .2539514
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0463857{col 31}{space 2} .0489428{col 42}{space 1}    0.95{col 51}{space 3}0.344{col 59}{space 4} -.049836{col 72}{space 3} .1426074
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0334925{col 31}{space 2} .0656954{col 42}{space 1}   -0.51{col 51}{space 3}0.610{col 59}{space 4}  -.16265{col 72}{space 3} .0956649
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6525041{col 31}{space 2} .1469903{col 42}{space 1}    4.44{col 51}{space 3}0.000{col 59}{space 4} .3635206{col 72}{space 3} .9414875
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       399
{txt}{hline 13}{c +}{hline 34}   F(4, 394)       = {res}     0.69
{txt}       Model {c |} {res} .196032421         4  .049008105   {txt}Prob > F        ={res}    0.6004
{txt}    Residual {c |} {res} 28.0520814       394  .071198176   {txt}R-squared       ={res}    0.0069
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0031
{txt}       Total {c |} {res} 28.2481138       398   .07097516   {txt}Root MSE        =   {res} .26683

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0396429{col 31}{space 2} .0412656{col 42}{space 1}   -0.96{col 51}{space 3}0.337{col 59}{space 4}-.1207712{col 72}{space 3} .0414854
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0040767{col 31}{space 2} .1324228{col 42}{space 1}    0.03{col 51}{space 3}0.975{col 59}{space 4}-.2562669{col 72}{space 3} .2644203
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0351898{col 31}{space 2} .0428597{col 42}{space 1}    0.82{col 51}{space 3}0.412{col 59}{space 4}-.0490725{col 72}{space 3} .1194522
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0611691{col 31}{space 2} .0575302{col 42}{space 1}    1.06{col 51}{space 3}0.288{col 59}{space 4}-.0519354{col 72}{space 3} .1742737
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7447887{col 31}{space 2}  .128721{col 42}{space 1}    5.79{col 51}{space 3}0.000{col 59}{space 4} .4917228{col 72}{space 3} .9978546
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       400
{txt}{hline 13}{c +}{hline 34}   F(4, 395)       = {res}     0.59
{txt}       Model {c |} {res} .204135447         4  .051033862   {txt}Prob > F        ={res}    0.6728
{txt}    Residual {c |} {res} 34.3896577       395  .087062425   {txt}R-squared       ={res}    0.0059
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0042
{txt}       Total {c |} {res} 34.5937932       399  .086701236   {txt}Root MSE        =   {res} .29506

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0357953{col 31}{space 2} .0454922{col 42}{space 1}   -0.79{col 51}{space 3}0.432{col 59}{space 4}-.1252324{col 72}{space 3} .0536418
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}  -.15384{col 31}{space 2} .1461748{col 42}{space 1}   -1.05{col 51}{space 3}0.293{col 59}{space 4}-.4412178{col 72}{space 3} .1335378
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} -.030235{col 31}{space 2} .0473005{col 42}{space 1}   -0.64{col 51}{space 3}0.523{col 59}{space 4}-.1232273{col 72}{space 3} .0627573
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0214798{col 31}{space 2} .0634617{col 42}{space 1}    0.34{col 51}{space 3}0.735{col 59}{space 4} -.103285{col 72}{space 3} .1462447
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8302587{col 31}{space 2}  .141955{col 42}{space 1}    5.85{col 51}{space 3}0.000{col 59}{space 4} .5511769{col 72}{space 3} 1.109341
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       398
{txt}{hline 13}{c +}{hline 34}   F(4, 393)       = {res}     1.27
{txt}       Model {c |} {res} .474133877         4  .118533469   {txt}Prob > F        ={res}    0.2809
{txt}    Residual {c |} {res} 36.6621262       393  .093287853   {txt}R-squared       ={res}    0.0128
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0027
{txt}       Total {c |} {res} 37.1362601       397  .093542217   {txt}Root MSE        =   {res} .30543

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0738527{col 31}{space 2} .0472908{col 42}{space 1}   -1.56{col 51}{space 3}0.119{col 59}{space 4}-.1668272{col 72}{space 3} .0191218
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} -.186725{col 31}{space 2} .1516876{col 42}{space 1}   -1.23{col 51}{space 3}0.219{col 59}{space 4}-.4849457{col 72}{space 3} .1114958
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0050121{col 31}{space 2} .0490769{col 42}{space 1}    0.10{col 51}{space 3}0.919{col 59}{space 4} -.091474{col 72}{space 3} .1014981
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0733142{col 31}{space 2} .0659212{col 42}{space 1}   -1.11{col 51}{space 3}0.267{col 59}{space 4}-.2029165{col 72}{space 3} .0562882
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8785729{col 31}{space 2} .1474869{col 42}{space 1}    5.96{col 51}{space 3}0.000{col 59}{space 4} .5886109{col 72}{space 3} 1.168535
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       400
{txt}{hline 13}{c +}{hline 34}   F(4, 395)       = {res}     0.63
{txt}       Model {c |} {res} .192164455         4  .048041114   {txt}Prob > F        ={res}    0.6404
{txt}    Residual {c |} {res} 30.0566097       395  .076092683   {txt}R-squared       ={res}    0.0064
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0037
{txt}       Total {c |} {res} 30.2487742       399  .075811464   {txt}Root MSE        =   {res} .27585

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0590677{col 31}{space 2} .0425298{col 42}{space 1}   -1.39{col 51}{space 3}0.166{col 59}{space 4}-.1426807{col 72}{space 3} .0245452
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0508728{col 31}{space 2} .1366559{col 42}{space 1}   -0.37{col 51}{space 3}0.710{col 59}{space 4}-.3195367{col 72}{space 3} .2177911
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0032089{col 31}{space 2} .0442204{col 42}{space 1}   -0.07{col 51}{space 3}0.942{col 59}{space 4}-.0901456{col 72}{space 3} .0837278
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0432068{col 31}{space 2} .0593291{col 42}{space 1}   -0.73{col 51}{space 3}0.467{col 59}{space 4} -.159847{col 72}{space 3} .0734335
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8112967{col 31}{space 2}  .132711{col 42}{space 1}    6.11{col 51}{space 3}0.000{col 59}{space 4} .5503885{col 72}{space 3} 1.072205
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       400
{txt}{hline 13}{c +}{hline 34}   F(4, 395)       = {res}     1.75
{txt}       Model {c |} {res} .572786192         4  .143196548   {txt}Prob > F        ={res}    0.1384
{txt}    Residual {c |} {res} 32.3348227       395  .081860311   {txt}R-squared       ={res}    0.0174
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0075
{txt}       Total {c |} {res} 32.9076088       399   .08247521   {txt}Root MSE        =   {res} .28611

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0371037{col 31}{space 2} .0441121{col 42}{space 1}   -0.84{col 51}{space 3}0.401{col 59}{space 4}-.1238276{col 72}{space 3} .0496203
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1245555{col 31}{space 2} .1417404{col 42}{space 1}   -0.88{col 51}{space 3}0.380{col 59}{space 4}-.4032154{col 72}{space 3} .1541045
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} -.023228{col 31}{space 2} .0458656{col 42}{space 1}   -0.51{col 51}{space 3}0.613{col 59}{space 4}-.1133993{col 72}{space 3} .0669433
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1369735{col 31}{space 2} .0615365{col 42}{space 1}    2.23{col 51}{space 3}0.027{col 59}{space 4} .0159935{col 72}{space 3} .2579535
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8197742{col 31}{space 2} .1376487{col 42}{space 1}    5.96{col 51}{space 3}0.000{col 59}{space 4} .5491585{col 72}{space 3}  1.09039
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. forval j=1/5 {c -(}
{txt}  2{com}. est table covid_gene_`j' covid_preexisting_`j' covid_jobs_`j' covid_healthcare_`j'  covid_neighborhood_`j' covid_flout_protocols_`j' , b(%9.2f) se style(col) eq(1) stats(N) keep(race_bio_identity pid7cata ed6cat age01 _cons)
{txt}  3{com}. est table covid_gene_`j' covid_preexisting_`j' covid_jobs_`j' covid_healthcare_`j'  covid_neighborhood_`j' covid_flout_protocols_`j' , b(%9.2f) star(.05 .01 .001) style(col) eq(1) stats(N) keep(race_bio_identity pid7cata ed6cat age01 _cons)
{txt}  4{com}. {c )-}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 9:covid_g~1} {c |} {center 9:covid_p~1} {c |} {center 9:covid_j~1} {c |} {center 9:covid_h~1} {c |} {center 9:covid_n~1} {c |} {center 9:covid_f~1} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}{res} {ralign 9:-0.00}{txt} {c |}{res} {ralign 9:-0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:-0.01}{txt} {c |}{res} {ralign 9:-0.19}{txt} {c |}{res} {ralign 9:-0.23}{txt} {c |}{res} {ralign 9:-0.09}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.12}{txt} {c |}{res} {ralign 9:0.09}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:-0.03}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.16}{txt} {c |}{res} {ralign 9:0.11}{txt} {c |}{res} {ralign 9:-0.02}{txt} {c |}{res} {ralign 9:-0.03}{txt} {c |}{res} {ralign 9:-0.01}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.08}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.56}{txt} {c |}{res} {ralign 9:0.70}{txt} {c |}{res} {ralign 9:0.79}{txt} {c |}{res} {ralign 9:0.87}{txt} {c |}{res} {ralign 9:0.76}{txt} {c |}{res} {ralign 9:0.72}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:371}{txt} {c |}{res} {ralign 9:371}{txt} {c |}{res} {ralign 9:371}{txt} {c |}{res} {ralign 9:371}{txt} {c |}{res} {ralign 9:371}{txt} {c |}{res} {ralign 9:371}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BRC}
{ralign 88:Legend: b/se}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 12:covid_gene_1} {c |} {center 12:covid_pree~1} {c |} {center 12:covid_jobs_1} {c |} {center 12:covid_heal~1} {c |} {center 12:covid_neig~1} {c |} {center 12:covid_flou~1} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:0.07}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:0.06}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.19}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.23}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.09}{lalign 3:*}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:0.12}{lalign 3:**}{txt} {c |}{res} {ralign 9:0.09}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.03}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.16}{lalign 3:*}{txt} {c |}{res} {ralign 9:0.11}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.56}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.70}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.79}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.87}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.76}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.72}{lalign 3:***}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:371}{lalign 3:}{txt} {c |}{res} {ralign 9:371}{lalign 3:}{txt} {c |}{res} {ralign 9:371}{lalign 3:}{txt} {c |}{res} {ralign 9:371}{lalign 3:}{txt} {c |}{res} {ralign 9:371}{lalign 3:}{txt} {c |}{res} {ralign 9:371}{lalign 3:}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BRC}
{ralign 106:Legend: * p<.05; ** p<.01; *** p<.001}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 9:covid_g~2} {c |} {center 9:covid_p~2} {c |} {center 9:covid_j~2} {c |} {center 9:covid_h~2} {c |} {center 9:covid_n~2} {c |} {center 9:covid_f~2} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.11}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.09}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.14}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.31}{txt} {c |}{res} {ralign 9:-0.12}{txt} {c |}{res} {ralign 9:-0.15}{txt} {c |}{res} {ralign 9:-0.12}{txt} {c |}{res} {ralign 9:-0.23}{txt} {c |}{res} {ralign 9:-0.21}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.10}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:-0.08}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.08}{txt} {c |}{res} {ralign 9:0.13}{txt} {c |}{res} {ralign 9:0.11}{txt} {c |}{res} {ralign 9:0.16}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.12}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.80}{txt} {c |}{res} {ralign 9:0.82}{txt} {c |}{res} {ralign 9:0.80}{txt} {c |}{res} {ralign 9:0.78}{txt} {c |}{res} {ralign 9:0.82}{txt} {c |}{res} {ralign 9:0.76}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:380}{txt} {c |}{res} {ralign 9:380}{txt} {c |}{res} {ralign 9:380}{txt} {c |}{res} {ralign 9:379}{txt} {c |}{res} {ralign 9:380}{txt} {c |}{res} {ralign 9:380}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BRC}
{ralign 88:Legend: b/se}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 12:covid_gene_2} {c |} {center 12:covid_pree~2} {c |} {center 12:covid_jobs_2} {c |} {center 12:covid_heal~2} {c |} {center 12:covid_neig~2} {c |} {center 12:covid_flou~2} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.11}{lalign 3:*}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.09}{lalign 3:**}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:0.14}{lalign 3:**}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.31}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.12}{lalign 3:**}{txt} {c |}{res} {ralign 9:-0.15}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.12}{lalign 3:**}{txt} {c |}{res} {ralign 9:-0.23}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.21}{lalign 3:***}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.10}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:0.06}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.08}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.08}{lalign 3:}{txt} {c |}{res} {ralign 9:0.13}{lalign 3:*}{txt} {c |}{res} {ralign 9:0.11}{lalign 3:*}{txt} {c |}{res} {ralign 9:0.16}{lalign 3:**}{txt} {c |}{res} {ralign 9:0.06}{lalign 3:}{txt} {c |}{res} {ralign 9:0.12}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.80}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.82}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.80}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.78}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.82}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.76}{lalign 3:***}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:380}{lalign 3:}{txt} {c |}{res} {ralign 9:380}{lalign 3:}{txt} {c |}{res} {ralign 9:380}{lalign 3:}{txt} {c |}{res} {ralign 9:379}{lalign 3:}{txt} {c |}{res} {ralign 9:380}{lalign 3:}{txt} {c |}{res} {ralign 9:380}{lalign 3:}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BRC}
{ralign 106:Legend: * p<.05; ** p<.01; *** p<.001}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 9:covid_g~3} {c |} {center 9:covid_p~3} {c |} {center 9:covid_j~3} {c |} {center 9:covid_h~3} {c |} {center 9:covid_n~3} {c |} {center 9:covid_f~3} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:-0.00}{txt} {c |}{res} {ralign 9:-0.02}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.17}{txt} {c |}{res} {ralign 9:-0.07}{txt} {c |}{res} {ralign 9:-0.18}{txt} {c |}{res} {ralign 9:-0.28}{txt} {c |}{res} {ralign 9:-0.18}{txt} {c |}{res} {ralign 9:-0.12}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.11}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:-0.00}{txt} {c |}{res} {ralign 9:-0.01}{txt} {c |}{res} {ralign 9:-0.01}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.05}{txt} {c |}{res} {ralign 9:0.12}{txt} {c |}{res} {ralign 9:0.10}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.10}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.08}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.78}{txt} {c |}{res} {ralign 9:0.80}{txt} {c |}{res} {ralign 9:0.82}{txt} {c |}{res} {ralign 9:0.87}{txt} {c |}{res} {ralign 9:0.88}{txt} {c |}{res} {ralign 9:0.81}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:360}{txt} {c |}{res} {ralign 9:361}{txt} {c |}{res} {ralign 9:360}{txt} {c |}{res} {ralign 9:361}{txt} {c |}{res} {ralign 9:360}{txt} {c |}{res} {ralign 9:361}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BRC}
{ralign 88:Legend: b/se}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 12:covid_gene_3} {c |} {center 12:covid_pree~3} {c |} {center 12:covid_jobs_3} {c |} {center 12:covid_heal~3} {c |} {center 12:covid_neig~3} {c |} {center 12:covid_flou~3} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.17}{lalign 3:**}{txt} {c |}{res} {ralign 9:-0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.18}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.28}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.18}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.12}{lalign 3:**}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.11}{lalign 3:}{txt} {c |}{res} {ralign 9:0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.01}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:0.12}{lalign 3:*}{txt} {c |}{res} {ralign 9:0.10}{lalign 3:}{txt} {c |}{res} {ralign 9:0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:0.06}{lalign 3:}{txt} {c |}{res} {ralign 9:0.10}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.78}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.80}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.82}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.87}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.88}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.81}{lalign 3:***}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:360}{lalign 3:}{txt} {c |}{res} {ralign 9:361}{lalign 3:}{txt} {c |}{res} {ralign 9:360}{lalign 3:}{txt} {c |}{res} {ralign 9:361}{lalign 3:}{txt} {c |}{res} {ralign 9:360}{lalign 3:}{txt} {c |}{res} {ralign 9:361}{lalign 3:}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BRC}
{ralign 106:Legend: * p<.05; ** p<.01; *** p<.001}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 9:covid_g~4} {c |} {center 9:covid_p~4} {c |} {center 9:covid_j~4} {c |} {center 9:covid_h~4} {c |} {center 9:covid_n~4} {c |} {center 9:covid_f~4} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.21}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:0.11}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:0.08}{txt} {c |}{res} {ralign 9:-0.20}{txt} {c |}{res} {ralign 9:-0.18}{txt} {c |}{res} {ralign 9:-0.12}{txt} {c |}{res} {ralign 9:-0.17}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.16}{txt} {c |}{res} {ralign 9:0.11}{txt} {c |}{res} {ralign 9:0.11}{txt} {c |}{res} {ralign 9:0.11}{txt} {c |}{res} {ralign 9:0.11}{txt} {c |}{res} {ralign 9:0.13}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.18}{txt} {c |}{res} {ralign 9:-0.00}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:-0.13}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:0.00}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.03}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:-0.02}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.63}{txt} {c |}{res} {ralign 9:0.78}{txt} {c |}{res} {ralign 9:0.78}{txt} {c |}{res} {ralign 9:0.81}{txt} {c |}{res} {ralign 9:0.84}{txt} {c |}{res} {ralign 9:0.77}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:407}{txt} {c |}{res} {ralign 9:407}{txt} {c |}{res} {ralign 9:407}{txt} {c |}{res} {ralign 9:407}{txt} {c |}{res} {ralign 9:407}{txt} {c |}{res} {ralign 9:407}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BRC}
{ralign 88:Legend: b/se}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 12:covid_gene_4} {c |} {center 12:covid_pree~4} {c |} {center 12:covid_jobs_4} {c |} {center 12:covid_heal~4} {c |} {center 12:covid_neig~4} {c |} {center 12:covid_flou~4} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.21}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.06}{lalign 3:}{txt} {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:0.11}{lalign 3:*}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:0.08}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.20}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.18}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.12}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.17}{lalign 3:}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:-0.18}{lalign 3:***}{txt} {c |}{res} {ralign 9:-0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.13}{lalign 3:***}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.63}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.78}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.78}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.81}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.84}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.77}{lalign 3:***}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:407}{lalign 3:}{txt} {c |}{res} {ralign 9:407}{lalign 3:}{txt} {c |}{res} {ralign 9:407}{lalign 3:}{txt} {c |}{res} {ralign 9:407}{lalign 3:}{txt} {c |}{res} {ralign 9:407}{lalign 3:}{txt} {c |}{res} {ralign 9:407}{lalign 3:}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BRC}
{ralign 106:Legend: * p<.05; ** p<.01; *** p<.001}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TT}{c -}{hline 9}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 9:covid_g~5} {c |} {center 9:covid_p~5} {c |} {center 9:covid_j~5} {c |} {center 9:covid_h~5} {c |} {center 9:covid_n~5} {c |} {center 9:covid_f~5} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}{res} {ralign 9:-0.07}{txt} {c |}{res} {ralign 9:-0.06}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.04}{txt} {c |}{res} {ralign 9:0.00}{txt} {c |}{res} {ralign 9:-0.15}{txt} {c |}{res} {ralign 9:-0.19}{txt} {c |}{res} {ralign 9:-0.05}{txt} {c |}{res} {ralign 9:-0.12}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.15}{txt} {c |}{res} {ralign 9:0.13}{txt} {c |}{res} {ralign 9:0.15}{txt} {c |}{res} {ralign 9:0.15}{txt} {c |}{res} {ralign 9:0.14}{txt} {c |}{res} {ralign 9:0.14}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:-0.03}{txt} {c |}{res} {ralign 9:0.01}{txt} {c |}{res} {ralign 9:-0.00}{txt} {c |}{res} {ralign 9:-0.02}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}{res} {ralign 9:0.04}{txt} {c |}{res} {ralign 9:0.05}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.03}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.02}{txt} {c |}{res} {ralign 9:-0.07}{txt} {c |}{res} {ralign 9:-0.04}{txt} {c |}{res} {ralign 9:0.14}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.07}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}{res} {ralign 9:0.06}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.65}{txt} {c |}{res} {ralign 9:0.74}{txt} {c |}{res} {ralign 9:0.83}{txt} {c |}{res} {ralign 9:0.88}{txt} {c |}{res} {ralign 9:0.81}{txt} {c |}{res} {ralign 9:0.82}{txt} {c |}
{res}{txt}{c |} {space 12} {c |}{res} {ralign 9:0.15}{txt} {c |}{res} {ralign 9:0.13}{txt} {c |}{res} {ralign 9:0.14}{txt} {c |}{res} {ralign 9:0.15}{txt} {c |}{res} {ralign 9:0.13}{txt} {c |}{res} {ralign 9:0.14}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c +}{c -}{hline 9}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:399}{txt} {c |}{res} {ralign 9:399}{txt} {c |}{res} {ralign 9:400}{txt} {c |}{res} {ralign 9:398}{txt} {c |}{res} {ralign 9:400}{txt} {c |}{res} {ralign 9:400}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BT}{c -}{hline 9}{c -}{c BRC}
{ralign 88:Legend: b/se}
{res}
{txt}{c TLC}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TT}{c -}{hline 12}{c -}{c TRC}
{c |} {ralign 12:Variable} {c |} {center 12:covid_gene_5} {c |} {center 12:covid_pree~5} {c |} {center 12:covid_jobs_5} {c |} {center 12:covid_heal~5} {c |} {center 12:covid_neig~5} {c |} {center 12:covid_flou~5} {c |}
{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{res}{txt}{c |} race_bio_i~y {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.06}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 4}pid7cata {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.15}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.19}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.12}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 6}ed6cat {c |}{res} {ralign 9:0.05}{lalign 3:}{txt} {c |}{res} {ralign 9:0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.01}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.00}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.02}{lalign 3:}{txt} {c |}
{res}{txt}{c |} {space 7}age01 {c |}{res} {ralign 9:-0.03}{lalign 3:}{txt} {c |}{res} {ralign 9:0.06}{lalign 3:}{txt} {c |}{res} {ralign 9:0.02}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.07}{lalign 3:}{txt} {c |}{res} {ralign 9:-0.04}{lalign 3:}{txt} {c |}{res} {ralign 9:0.14}{lalign 3:*}{txt} {c |}
{res}{txt}{c |} {space 7}_cons {c |}{res} {ralign 9:0.65}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.74}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.83}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.88}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.81}{lalign 3:***}{txt} {c |}{res} {ralign 9:0.82}{lalign 3:***}{txt} {c |}
{res}{txt}{c LT}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c +}{c -}{hline 12}{c -}{c RT}
{c |} {ralign 12:N} {c |}{res} {ralign 9:399}{lalign 3:}{txt} {c |}{res} {ralign 9:399}{lalign 3:}{txt} {c |}{res} {ralign 9:400}{lalign 3:}{txt} {c |}{res} {ralign 9:398}{lalign 3:}{txt} {c |}{res} {ralign 9:400}{lalign 3:}{txt} {c |}{res} {ralign 9:400}{lalign 3:}{txt} {c |}
{res}{txt}{c BLC}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c BRC}
{ralign 106:Legend: * p<.05; ** p<.01; *** p<.001}
{res}{txt}
{com}. 
. 
. **********FOOTNOTE - SEPARATE SAMPLE ESTIMATION
. //pairwise comparisons:
. //looking at the effect of race_bio_identity among:
. //Asians vs. Blacks, Hispanics, W Dem, W GOP
. //Blacks vs. Hispanics, W Dem, W GOP
. //Hispanics vs. W Dem, W GOP
. //W Dem vs. W GOP
. *10 total comparisons
. 
. forval j=1/5 {c -(}
{txt}  2{com}.         foreach v of varlist covid_gene covid_preexisting covid_jobs covid_healthcare covid_neighborhood covid_flout_protocols {c -(}
{txt}  3{com}.         reg `v' race_bio_identity pid7cata ed6cat age01 black hispanic api if fivegroups==`j' & ref_covid_battery~=6
{txt}  4{com}. est store `v'`j'
{txt}  5{com}.         {c )-}
{txt}  6{com}.         {c )-}
{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     1.45
{txt}       Model {c |} {res} .579246558         4   .14481164   {txt}Prob > F        ={res}    0.2167
{txt}    Residual {c |} {res} 36.5315635       366  .099813015   {txt}R-squared       ={res}    0.0156
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0049
{txt}       Total {c |} {res}   37.11081       370  .100299487   {txt}Root MSE        =   {res} .31593

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0324745{col 31}{space 2} .0568972{col 42}{space 1}    0.57{col 51}{space 3}0.569{col 59}{space 4} -.079412{col 72}{space 3}  .144361
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0591964{col 31}{space 2} .0527821{col 42}{space 1}    1.12{col 51}{space 3}0.263{col 59}{space 4}-.0445978{col 72}{space 3} .1629905
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0742419{col 31}{space 2} .0588599{col 42}{space 1}    1.26{col 51}{space 3}0.208{col 59}{space 4}-.0415041{col 72}{space 3} .1899879
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.1568964{col 31}{space 2} .0781705{col 42}{space 1}   -2.01{col 51}{space 3}0.045{col 59}{space 4}-.3106161{col 72}{space 3}-.0031768
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .5631289{col 31}{space 2} .0609746{col 42}{space 1}    9.24{col 51}{space 3}0.000{col 59}{space 4} .4432244{col 72}{space 3} .6830334
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     3.60
{txt}       Model {c |} {res}  .81048245         4  .202620613   {txt}Prob > F        ={res}    0.0068
{txt}    Residual {c |} {res} 20.6139349       366  .056322226   {txt}R-squared       ={res}    0.0378
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0273
{txt}       Total {c |} {res} 21.4244173       370  .057903831   {txt}Root MSE        =   {res} .23732

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0398849{col 31}{space 2} .0427403{col 42}{space 1}   -0.93{col 51}{space 3}0.351{col 59}{space 4}-.1239322{col 72}{space 3} .0441624
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0054818{col 31}{space 2}  .039649{col 42}{space 1}   -0.14{col 51}{space 3}0.890{col 59}{space 4}-.0834503{col 72}{space 3} .0724867
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .1194409{col 31}{space 2} .0442146{col 42}{space 1}    2.70{col 51}{space 3}0.007{col 59}{space 4} .0324944{col 72}{space 3} .2063875
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1065469{col 31}{space 2} .0587204{col 42}{space 1}    1.81{col 51}{space 3}0.070{col 59}{space 4}-.0089248{col 72}{space 3} .2220186
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7016881{col 31}{space 2} .0458031{col 42}{space 1}   15.32{col 51}{space 3}0.000{col 59}{space 4} .6116178{col 72}{space 3} .7917585
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     5.93
{txt}       Model {c |} {res} 1.67427775         4  .418569437   {txt}Prob > F        ={res}    0.0001
{txt}    Residual {c |} {res} 25.8509623       366  .070631045   {txt}R-squared       ={res}    0.0608
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0506
{txt}       Total {c |} {res} 27.5252401       370  .074392541   {txt}Root MSE        =   {res} .26577

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0009218{col 31}{space 2} .0478625{col 42}{space 1}   -0.02{col 51}{space 3}0.985{col 59}{space 4}-.0950418{col 72}{space 3} .0931982
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1862137{col 31}{space 2} .0444008{col 42}{space 1}   -4.19{col 51}{space 3}0.000{col 59}{space 4}-.2735264{col 72}{space 3}-.0989011
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0851424{col 31}{space 2} .0495135{col 42}{space 1}    1.72{col 51}{space 3}0.086{col 59}{space 4}-.0122242{col 72}{space 3} .1825091
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0157478{col 31}{space 2} .0657578{col 42}{space 1}   -0.24{col 51}{space 3}0.811{col 59}{space 4}-.1450582{col 72}{space 3} .1135627
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2}  .785093{col 31}{space 2} .0512924{col 42}{space 1}   15.31{col 51}{space 3}0.000{col 59}{space 4} .6842281{col 72}{space 3} .8859578
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     7.39
{txt}       Model {c |} {res} 2.04979012         4  .512447531   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 25.3731616       366  .069325578   {txt}R-squared       ={res}    0.0747
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0646
{txt}       Total {c |} {res} 27.4229517       370  .074116086   {txt}Root MSE        =   {res}  .2633

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0325693{col 31}{space 2} .0474181{col 42}{space 1}   -0.69{col 51}{space 3}0.493{col 59}{space 4}-.1258154{col 72}{space 3} .0606768
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} -.229716{col 31}{space 2} .0439885{col 42}{space 1}   -5.22{col 51}{space 3}0.000{col 59}{space 4} -.316218{col 72}{space 3} -.143214
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0089697{col 31}{space 2} .0490538{col 42}{space 1}    0.18{col 51}{space 3}0.855{col 59}{space 4} -.087493{col 72}{space 3} .1054323
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0278694{col 31}{space 2} .0651472{col 42}{space 1}   -0.43{col 51}{space 3}0.669{col 59}{space 4}-.1559792{col 72}{space 3} .1002405
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8691811{col 31}{space 2} .0508162{col 42}{space 1}   17.10{col 51}{space 3}0.000{col 59}{space 4} .7692527{col 72}{space 3} .9691094
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     1.62
{txt}       Model {c |} {res}  .39584855         4  .098962138   {txt}Prob > F        ={res}    0.1673
{txt}    Residual {c |} {res}  22.289605       366   .06090056   {txt}R-squared       ={res}    0.0174
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0067
{txt}       Total {c |} {res} 22.6854535       370  .061312037   {txt}Root MSE        =   {res} .24678

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0167589{col 31}{space 2} .0444435{col 42}{space 1}    0.38{col 51}{space 3}0.706{col 59}{space 4}-.0706377{col 72}{space 3} .1041556
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0870414{col 31}{space 2} .0412291{col 42}{space 1}   -2.11{col 51}{space 3}0.035{col 59}{space 4} -.168117{col 72}{space 3}-.0059658
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0454811{col 31}{space 2} .0459766{col 42}{space 1}    0.99{col 51}{space 3}0.323{col 59}{space 4}-.0449302{col 72}{space 3} .1358925
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0149529{col 31}{space 2} .0610604{col 42}{space 1}   -0.24{col 51}{space 3}0.807{col 59}{space 4}-.1350262{col 72}{space 3} .1051204
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7603401{col 31}{space 2} .0476284{col 42}{space 1}   15.96{col 51}{space 3}0.000{col 59}{space 4} .6666804{col 72}{space 3} .8539997
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       371
{txt}{hline 13}{c +}{hline 34}   F(4, 366)       = {res}     0.73
{txt}       Model {c |} {res} .234894137         4  .058723534   {txt}Prob > F        ={res}    0.5689
{txt}    Residual {c |} {res} 29.2611228       366  .079948423   {txt}R-squared       ={res}    0.0080
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0029
{txt}       Total {c |} {res} 29.4960169       370  .079718965   {txt}Root MSE        =   {res} .28275

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0684512{col 31}{space 2} .0509216{col 42}{space 1}    1.34{col 51}{space 3}0.180{col 59}{space 4}-.0316845{col 72}{space 3} .1685869
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0430464{col 31}{space 2} .0472387{col 42}{space 1}   -0.91{col 51}{space 3}0.363{col 59}{space 4}-.1359397{col 72}{space 3} .0498468
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} -.033915{col 31}{space 2} .0526782{col 42}{space 1}   -0.64{col 51}{space 3}0.520{col 59}{space 4}-.1375049{col 72}{space 3} .0696749
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0434023{col 31}{space 2} .0699607{col 42}{space 1}    0.62{col 51}{space 3}0.535{col 59}{space 4}-.0941731{col 72}{space 3} .1809777
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7210282{col 31}{space 2} .0545708{col 42}{space 1}   13.21{col 51}{space 3}0.000{col 59}{space 4} .6137166{col 72}{space 3} .8283399
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     8.73
{txt}       Model {c |} {res} 3.71725623         4  .929314057   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 39.9013221       375  .106403526   {txt}R-squared       ={res}    0.0852
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0755
{txt}       Total {c |} {res} 43.6185783       379  .115088597   {txt}Root MSE        =   {res}  .3262

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .1058281{col 31}{space 2} .0510399{col 42}{space 1}    2.07{col 51}{space 3}0.039{col 59}{space 4} .0054678{col 72}{space 3} .2061884
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.3057266{col 31}{space 2} .0621366{col 42}{space 1}   -4.92{col 51}{space 3}0.000{col 59}{space 4}-.4279064{col 72}{space 3}-.1835468
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0999222{col 31}{space 2} .0585648{col 42}{space 1}   -1.71{col 51}{space 3}0.089{col 59}{space 4}-.2150788{col 72}{space 3} .0152345
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0823343{col 31}{space 2} .0738895{col 42}{space 1}   -1.11{col 51}{space 3}0.266{col 59}{space 4} -.227624{col 72}{space 3} .0629555
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7988455{col 31}{space 2} .0514093{col 42}{space 1}   15.54{col 51}{space 3}0.000{col 59}{space 4} .6977589{col 72}{space 3} .8999321
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     4.60
{txt}       Model {c |} {res} .953243977         4  .238310994   {txt}Prob > F        ={res}    0.0012
{txt}    Residual {c |} {res} 19.4162107       375  .051776562   {txt}R-squared       ={res}    0.0468
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0366
{txt}       Total {c |} {res} 20.3694547       379  .053745263   {txt}Root MSE        =   {res} .22754

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0313973{col 31}{space 2}  .035604{col 42}{space 1}    0.88{col 51}{space 3}0.378{col 59}{space 4}-.0386111{col 72}{space 3} .1014058
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1227863{col 31}{space 2} .0433447{col 42}{space 1}   -2.83{col 51}{space 3}0.005{col 59}{space 4}-.2080154{col 72}{space 3}-.0375572
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0112409{col 31}{space 2} .0408532{col 42}{space 1}    0.28{col 51}{space 3}0.783{col 59}{space 4}-.0690891{col 72}{space 3} .0915709
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .128478{col 31}{space 2} .0515432{col 42}{space 1}    2.49{col 51}{space 3}0.013{col 59}{space 4}  .027128{col 72}{space 3} .2298279
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8195459{col 31}{space 2} .0358617{col 42}{space 1}   22.85{col 51}{space 3}0.000{col 59}{space 4} .7490308{col 72}{space 3}  .890061
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     8.43
{txt}       Model {c |} {res} 1.44288195         4  .360720487   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 16.0441898       375  .042784506   {txt}R-squared       ={res}    0.0825
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0727
{txt}       Total {c |} {res} 17.4870717       379  .046140031   {txt}Root MSE        =   {res} .20684

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0877688{col 31}{space 2}  .032365{col 42}{space 1}    2.71{col 51}{space 3}0.007{col 59}{space 4} .0241292{col 72}{space 3} .1514083
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1531162{col 31}{space 2} .0394015{col 42}{space 1}   -3.89{col 51}{space 3}0.000{col 59}{space 4}-.2305918{col 72}{space 3}-.0756407
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0199343{col 31}{space 2} .0371366{col 42}{space 1}    0.54{col 51}{space 3}0.592{col 59}{space 4}-.0530878{col 72}{space 3} .0929563
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1145094{col 31}{space 2} .0468542{col 42}{space 1}    2.44{col 51}{space 3}0.015{col 59}{space 4} .0223796{col 72}{space 3} .2066392
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8019836{col 31}{space 2} .0325992{col 42}{space 1}   24.60{col 51}{space 3}0.000{col 59}{space 4} .7378835{col 72}{space 3} .8660838
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       379
{txt}{hline 13}{c +}{hline 34}   F(4, 374)       = {res}     6.98
{txt}       Model {c |} {res} 1.40336645         4  .350841612   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.7894744       374  .050239236   {txt}R-squared       ={res}    0.0695
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0595
{txt}       Total {c |} {res} 20.1928408       378  .053420214   {txt}Root MSE        =   {res} .22414

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0318773{col 31}{space 2} .0351275{col 42}{space 1}    0.91{col 51}{space 3}0.365{col 59}{space 4}-.0371948{col 72}{space 3} .1009495
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1167946{col 31}{space 2} .0427444{col 42}{space 1}   -2.73{col 51}{space 3}0.007{col 59}{space 4}-.2008441{col 72}{space 3}-.0327451
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0719376{col 31}{space 2} .0402421{col 42}{space 1}    1.79{col 51}{space 3}0.075{col 59}{space 4}-.0071916{col 72}{space 3} .1510667
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1609723{col 31}{space 2}  .050811{col 42}{space 1}    3.17{col 51}{space 3}0.002{col 59}{space 4} .0610613{col 72}{space 3} .2608834
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7835973{col 31}{space 2} .0354449{col 42}{space 1}   22.11{col 51}{space 3}0.000{col 59}{space 4} .7139011{col 72}{space 3} .8532935
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}    10.04
{txt}       Model {c |} {res} 2.03008062         4  .507520156   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.9610267       375  .050562738   {txt}R-squared       ={res}    0.0967
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0871
{txt}       Total {c |} {res} 20.9911073       379  .055385507   {txt}Root MSE        =   {res} .22486

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0517345{col 31}{space 2} .0351842{col 42}{space 1}    1.47{col 51}{space 3}0.142{col 59}{space 4}-.0174484{col 72}{space 3} .1209175
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.2347881{col 31}{space 2} .0428336{col 42}{space 1}   -5.48{col 51}{space 3}0.000{col 59}{space 4}-.3190123{col 72}{space 3} -.150564
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0607888{col 31}{space 2} .0403714{col 42}{space 1}    1.51{col 51}{space 3}0.133{col 59}{space 4} -.018594{col 72}{space 3} .1401715
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0594472{col 31}{space 2} .0509355{col 42}{space 1}    1.17{col 51}{space 3}0.244{col 59}{space 4}-.0407077{col 72}{space 3} .1596022
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8220856{col 31}{space 2} .0354388{col 42}{space 1}   23.20{col 51}{space 3}0.000{col 59}{space 4} .7524019{col 72}{space 3} .8917692
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       380
{txt}{hline 13}{c +}{hline 34}   F(4, 375)       = {res}     8.95
{txt}       Model {c |} {res} 2.64789078         4  .661972695   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 27.7336231       375  .073956328   {txt}R-squared       ={res}    0.0872
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0774
{txt}       Total {c |} {res} 30.3815139       379  .080162306   {txt}Root MSE        =   {res} .27195

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .1361745{col 31}{space 2}  .042552{col 42}{space 1}    3.20{col 51}{space 3}0.001{col 59}{space 4} .0525042{col 72}{space 3} .2198449
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.2100863{col 31}{space 2} .0518033{col 42}{space 1}   -4.06{col 51}{space 3}0.000{col 59}{space 4}-.3119475{col 72}{space 3} -.108225
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0753691{col 31}{space 2} .0488255{col 42}{space 1}   -1.54{col 51}{space 3}0.124{col 59}{space 4}-.1713752{col 72}{space 3}  .020637
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1183134{col 31}{space 2} .0616017{col 42}{space 1}    1.92{col 51}{space 3}0.056{col 59}{space 4}-.0028146{col 72}{space 3} .2394415
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7589043{col 31}{space 2} .0428599{col 42}{space 1}   17.71{col 51}{space 3}0.000{col 59}{space 4} .6746284{col 72}{space 3} .8431801
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       360
{txt}{hline 13}{c +}{hline 34}   F(4, 355)       = {res}     4.07
{txt}       Model {c |} {res} 1.64947521         4  .412368804   {txt}Prob > F        ={res}    0.0031
{txt}    Residual {c |} {res} 35.9907439       355  .101382377   {txt}R-squared       ={res}    0.0438
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0330
{txt}       Total {c |} {res} 37.6402192       359  .104847407   {txt}Root MSE        =   {res} .31841

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0533694{col 31}{space 2} .0519445{col 42}{space 1}    1.03{col 51}{space 3}0.305{col 59}{space 4}-.0487882{col 72}{space 3} .1555271
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1659894{col 31}{space 2} .0508141{col 42}{space 1}   -3.27{col 51}{space 3}0.001{col 59}{space 4}-.2659238{col 72}{space 3} -.066055
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1071097{col 31}{space 2} .0595468{col 42}{space 1}   -1.80{col 51}{space 3}0.073{col 59}{space 4}-.2242185{col 72}{space 3} .0099992
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0473796{col 31}{space 2} .0787381{col 42}{space 1}   -0.60{col 51}{space 3}0.548{col 59}{space 4}-.2022314{col 72}{space 3} .1074722
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7841609{col 31}{space 2} .0524649{col 42}{space 1}   14.95{col 51}{space 3}0.000{col 59}{space 4} .6809797{col 72}{space 3} .8873421
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       361
{txt}{hline 13}{c +}{hline 34}   F(4, 356)       = {res}     3.23
{txt}       Model {c |} {res} .653859767         4  .163464942   {txt}Prob > F        ={res}    0.0126
{txt}    Residual {c |} {res} 17.9907714       356  .050535875   {txt}R-squared       ={res}    0.0351
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0242
{txt}       Total {c |} {res} 18.6446312       360  .051790642   {txt}Root MSE        =   {res}  .2248

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0029366{col 31}{space 2} .0366683{col 42}{space 1}   -0.08{col 51}{space 3}0.936{col 59}{space 4}-.0750503{col 72}{space 3}  .069177
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0704206{col 31}{space 2} .0358637{col 42}{space 1}   -1.96{col 51}{space 3}0.050{col 59}{space 4} -.140952{col 72}{space 3} .0001108
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0678801{col 31}{space 2} .0420408{col 42}{space 1}    1.61{col 51}{space 3}0.107{col 59}{space 4}-.0147994{col 72}{space 3} .1505597
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1217662{col 31}{space 2} .0555895{col 42}{space 1}    2.19{col 51}{space 3}0.029{col 59}{space 4} .0124411{col 72}{space 3} .2310912
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7953463{col 31}{space 2} .0370303{col 42}{space 1}   21.48{col 51}{space 3}0.000{col 59}{space 4} .7225206{col 72}{space 3}  .868172
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       360
{txt}{hline 13}{c +}{hline 34}   F(4, 355)       = {res}     5.46
{txt}       Model {c |} {res} 1.54359277         4  .385898192   {txt}Prob > F        ={res}    0.0003
{txt}    Residual {c |} {res} 25.0849664       355  .070661877   {txt}R-squared       ={res}    0.0580
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0474
{txt}       Total {c |} {res} 26.6285591       359  .074174259   {txt}Root MSE        =   {res} .26582

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0197356{col 31}{space 2} .0433662{col 42}{space 1}   -0.46{col 51}{space 3}0.649{col 59}{space 4}-.1050225{col 72}{space 3} .0655512
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1817085{col 31}{space 2} .0424224{col 42}{space 1}   -4.28{col 51}{space 3}0.000{col 59}{space 4}-.2651393{col 72}{space 3}-.0982777
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0333824{col 31}{space 2}  .049713{col 42}{space 1}    0.67{col 51}{space 3}0.502{col 59}{space 4}-.0643865{col 72}{space 3} .1311514
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1028598{col 31}{space 2}  .065735{col 42}{space 1}    1.56{col 51}{space 3}0.119{col 59}{space 4}-.0264191{col 72}{space 3} .2321387
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8173275{col 31}{space 2} .0438006{col 42}{space 1}   18.66{col 51}{space 3}0.000{col 59}{space 4} .7311862{col 72}{space 3} .9034689
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       361
{txt}{hline 13}{c +}{hline 34}   F(4, 356)       = {res}    11.92
{txt}       Model {c |} {res}  3.1784622         4   .79461555   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 23.7387248       356  .066681811   {txt}R-squared       ={res}    0.1181
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1082
{txt}       Total {c |} {res}  26.917187       360  .074769964   {txt}Root MSE        =   {res} .25823

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0067312{col 31}{space 2} .0421206{col 42}{space 1}    0.16{col 51}{space 3}0.873{col 59}{space 4}-.0761052{col 72}{space 3} .0895676
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.2833748{col 31}{space 2} .0411964{col 42}{space 1}   -6.88{col 51}{space 3}0.000{col 59}{space 4}-.3643937{col 72}{space 3}-.2023558
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0040141{col 31}{space 2}  .048292{col 42}{space 1}   -0.08{col 51}{space 3}0.934{col 59}{space 4}-.0989875{col 72}{space 3} .0909592
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .066689{col 31}{space 2} .0638552{col 42}{space 1}    1.04{col 51}{space 3}0.297{col 59}{space 4}-.0588919{col 72}{space 3} .1922699
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8653796{col 31}{space 2} .0425365{col 42}{space 1}   20.34{col 51}{space 3}0.000{col 59}{space 4} .7817253{col 72}{space 3} .9490339
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       360
{txt}{hline 13}{c +}{hline 34}   F(4, 355)       = {res}     5.53
{txt}       Model {c |} {res} 1.41011266         4  .352528166   {txt}Prob > F        ={res}    0.0002
{txt}    Residual {c |} {res} 22.6211965       355   .06372168   {txt}R-squared       ={res}    0.0587
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0481
{txt}       Total {c |} {res} 24.0313092       359   .06693958   {txt}Root MSE        =   {res} .25243

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0356082{col 31}{space 2} .0411815{col 42}{space 1}   -0.86{col 51}{space 3}0.388{col 59}{space 4}-.1165985{col 72}{space 3} .0453822
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1820329{col 31}{space 2} .0402853{col 42}{space 1}   -4.52{col 51}{space 3}0.000{col 59}{space 4}-.2612607{col 72}{space 3}-.1028051
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0073862{col 31}{space 2} .0472086{col 42}{space 1}   -0.16{col 51}{space 3}0.876{col 59}{space 4}-.1002298{col 72}{space 3} .0854574
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0604398{col 31}{space 2} .0624234{col 42}{space 1}    0.97{col 51}{space 3}0.334{col 59}{space 4}-.0623263{col 72}{space 3}  .183206
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8818313{col 31}{space 2} .0415941{col 42}{space 1}   21.20{col 51}{space 3}0.000{col 59}{space 4} .8000295{col 72}{space 3} .9636331
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       361
{txt}{hline 13}{c +}{hline 34}   F(4, 356)       = {res}     2.19
{txt}       Model {c |} {res}  .67025829         4  .167564573   {txt}Prob > F        ={res}    0.0699
{txt}    Residual {c |} {res} 27.2619763       356  .076578585   {txt}R-squared       ={res}    0.0240
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0130
{txt}       Total {c |} {res} 27.9322346       360  .077589541   {txt}Root MSE        =   {res} .27673

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0229041{col 31}{space 2} .0451382{col 42}{space 1}    0.51{col 51}{space 3}0.612{col 59}{space 4}-.0658669{col 72}{space 3} .1116751
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1194934{col 31}{space 2} .0441478{col 42}{space 1}   -2.71{col 51}{space 3}0.007{col 59}{space 4}-.2063168{col 72}{space 3}-.0326701
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0140755{col 31}{space 2} .0517517{col 42}{space 1}   -0.27{col 51}{space 3}0.786{col 59}{space 4} -.115853{col 72}{space 3} .0877021
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1014652{col 31}{space 2}   .06843{col 42}{space 1}    1.48{col 51}{space 3}0.139{col 59}{space 4}-.0331126{col 72}{space 3} .2360431
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8061818{col 31}{space 2} .0455839{col 42}{space 1}   17.69{col 51}{space 3}0.000{col 59}{space 4} .7165342{col 72}{space 3} .8958293
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     7.42
{txt}       Model {c |} {res} 2.98877648         4   .74719412   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  40.467252       402  .100664806   {txt}R-squared       ={res}    0.0688
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0595
{txt}       Total {c |} {res} 43.4560284       406  .107034553   {txt}Root MSE        =   {res} .31728

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .2133851{col 31}{space 2} .0515421{col 42}{space 1}    4.14{col 51}{space 3}0.000{col 59}{space 4} .1120593{col 72}{space 3} .3147108
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0846483{col 31}{space 2} .1596313{col 42}{space 1}    0.53{col 51}{space 3}0.596{col 59}{space 4}-.2291681{col 72}{space 3} .3984647
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1760361{col 31}{space 2} .0467479{col 42}{space 1}   -3.77{col 51}{space 3}0.000{col 59}{space 4}-.2679369{col 72}{space 3}-.0841352
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .002533{col 31}{space 2} .0659922{col 42}{space 1}    0.04{col 51}{space 3}0.969{col 59}{space 4}-.1271999{col 72}{space 3}  .132266
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6271268{col 31}{space 2} .0567527{col 42}{space 1}   11.05{col 51}{space 3}0.000{col 59}{space 4} .5155576{col 72}{space 3}  .738696
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     2.28
{txt}       Model {c |} {res} .412443651         4  .103110913   {txt}Prob > F        ={res}    0.0597
{txt}    Residual {c |} {res} 18.1452058       402  .045137328   {txt}R-squared       ={res}    0.0222
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0125
{txt}       Total {c |} {res} 18.5576495       406  .045708496   {txt}Root MSE        =   {res} .21246

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0573509{col 31}{space 2} .0345137{col 42}{space 1}    1.66{col 51}{space 3}0.097{col 59}{space 4} -.010499{col 72}{space 3} .1252007
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1970412{col 31}{space 2} .1068925{col 42}{space 1}   -1.84{col 51}{space 3}0.066{col 59}{space 4}-.4071793{col 72}{space 3} .0130968
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0019346{col 31}{space 2} .0313034{col 42}{space 1}   -0.06{col 51}{space 3}0.951{col 59}{space 4}-.0634734{col 72}{space 3} .0596041
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0722703{col 31}{space 2} .0441898{col 42}{space 1}    1.64{col 51}{space 3}0.103{col 59}{space 4}-.0146016{col 72}{space 3} .1591422
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7817348{col 31}{space 2} .0380028{col 42}{space 1}   20.57{col 51}{space 3}0.000{col 59}{space 4} .7070258{col 72}{space 3} .8564439
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     2.00
{txt}       Model {c |} {res} .404118445         4  .101029611   {txt}Prob > F        ={res}    0.0944
{txt}    Residual {c |} {res} 20.3488663       402   .05061907   {txt}R-squared       ={res}    0.0195
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0097
{txt}       Total {c |} {res} 20.7529847       406  .051115726   {txt}Root MSE        =   {res} .22499

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0547933{col 31}{space 2} .0365494{col 42}{space 1}    1.50{col 51}{space 3}0.135{col 59}{space 4}-.0170586{col 72}{space 3} .1266452
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} -.182361{col 31}{space 2} .1131974{col 42}{space 1}   -1.61{col 51}{space 3}0.108{col 59}{space 4}-.4048938{col 72}{space 3} .0401717
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0407347{col 31}{space 2} .0331497{col 42}{space 1}    1.23{col 51}{space 3}0.220{col 59}{space 4}-.0244338{col 72}{space 3} .1059032
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0324152{col 31}{space 2} .0467962{col 42}{space 1}    0.69{col 51}{space 3}0.489{col 59}{space 4}-.0595807{col 72}{space 3} .1244111
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7821882{col 31}{space 2} .0402444{col 42}{space 1}   19.44{col 51}{space 3}0.000{col 59}{space 4} .7030725{col 72}{space 3} .8613038
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     1.12
{txt}       Model {c |} {res} .217652612         4  .054413153   {txt}Prob > F        ={res}    0.3462
{txt}    Residual {c |} {res} 19.5187075       402  .048553999   {txt}R-squared       ={res}    0.0110
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0012
{txt}       Total {c |} {res} 19.7363601       406  .048611724   {txt}Root MSE        =   {res} .22035

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0252626{col 31}{space 2} .0357961{col 42}{space 1}    0.71{col 51}{space 3}0.481{col 59}{space 4}-.0451084{col 72}{space 3} .0956335
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1203537{col 31}{space 2} .1108643{col 42}{space 1}   -1.09{col 51}{space 3}0.278{col 59}{space 4}-.3382999{col 72}{space 3} .0975925
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}   .04375{col 31}{space 2} .0324665{col 42}{space 1}    1.35{col 51}{space 3}0.179{col 59}{space 4}-.0200753{col 72}{space 3} .1075754
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0241993{col 31}{space 2} .0458317{col 42}{space 1}    0.53{col 51}{space 3}0.598{col 59}{space 4}-.0659006{col 72}{space 3} .1142991
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8130975{col 31}{space 2} .0394149{col 42}{space 1}   20.63{col 51}{space 3}0.000{col 59}{space 4} .7356124{col 72}{space 3} .8905826
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     0.84
{txt}       Model {c |} {res} .156200442         4  .039050111   {txt}Prob > F        ={res}    0.4986
{txt}    Residual {c |} {res} 18.6263734       402  .046334262   {txt}R-squared       ={res}    0.0083
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0016
{txt}       Total {c |} {res} 18.7825738       406  .046262497   {txt}Root MSE        =   {res} .21525

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0210827{col 31}{space 2} .0349683{col 42}{space 1}    0.60{col 51}{space 3}0.547{col 59}{space 4}-.0476609{col 72}{space 3} .0898262
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1740544{col 31}{space 2} .1083005{col 42}{space 1}   -1.61{col 51}{space 3}0.109{col 59}{space 4}-.3869605{col 72}{space 3} .0388516
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0065647{col 31}{space 2} .0317157{col 42}{space 1}    0.21{col 51}{space 3}0.836{col 59}{space 4}-.0557847{col 72}{space 3}  .068914
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0175605{col 31}{space 2} .0447718{col 42}{space 1}   -0.39{col 51}{space 3}0.695{col 59}{space 4}-.1055767{col 72}{space 3} .0704557
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8352892{col 31}{space 2} .0385034{col 42}{space 1}   21.69{col 51}{space 3}0.000{col 59}{space 4} .7595961{col 72}{space 3} .9109824
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       407
{txt}{hline 13}{c +}{hline 34}   F(4, 402)       = {res}     4.09
{txt}       Model {c |} {res} 1.12909941         4  .282274851   {txt}Prob > F        ={res}    0.0029
{txt}    Residual {c |} {res} 27.7268853       402  .068972351   {txt}R-squared       ={res}    0.0391
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0296
{txt}       Total {c |} {res} 28.8559847       406  .071073854   {txt}Root MSE        =   {res} .26263

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .1066946{col 31}{space 2} .0426639{col 42}{space 1}    2.50{col 51}{space 3}0.013{col 59}{space 4} .0228223{col 72}{space 3} .1905669
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0273028{col 31}{space 2} .1321347{col 42}{space 1}    0.21{col 51}{space 3}0.836{col 59}{space 4}-.2324584{col 72}{space 3}  .287064
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1284749{col 31}{space 2} .0386955{col 42}{space 1}   -3.32{col 51}{space 3}0.001{col 59}{space 4}-.2045458{col 72}{space 3}-.0524041
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0097445{col 31}{space 2}  .054625{col 42}{space 1}    0.18{col 51}{space 3}0.859{col 59}{space 4}-.0976418{col 72}{space 3} .1171308
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7685589{col 31}{space 2}  .046977{col 42}{space 1}   16.36{col 51}{space 3}0.000{col 59}{space 4} .6762076{col 72}{space 3} .8609102
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       399
{txt}{hline 13}{c +}{hline 34}   F(4, 394)       = {res}     0.45
{txt}       Model {c |} {res}  .16765988         4   .04191497   {txt}Prob > F        ={res}    0.7713
{txt}    Residual {c |} {res} 36.5800093       394  .092842663   {txt}R-squared       ={res}    0.0046
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0055
{txt}       Total {c |} {res} 36.7476692       398  .092330827   {txt}Root MSE        =   {res}  .3047

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0202144{col 31}{space 2} .0471224{col 42}{space 1}    0.43{col 51}{space 3}0.668{col 59}{space 4}-.0724284{col 72}{space 3} .1128572
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0433427{col 31}{space 2} .1512175{col 42}{space 1}   -0.29{col 51}{space 3}0.775{col 59}{space 4}-.3406367{col 72}{space 3} .2539514
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0463857{col 31}{space 2} .0489428{col 42}{space 1}    0.95{col 51}{space 3}0.344{col 59}{space 4} -.049836{col 72}{space 3} .1426074
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0334925{col 31}{space 2} .0656954{col 42}{space 1}   -0.51{col 51}{space 3}0.610{col 59}{space 4}  -.16265{col 72}{space 3} .0956649
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6525041{col 31}{space 2} .1469903{col 42}{space 1}    4.44{col 51}{space 3}0.000{col 59}{space 4} .3635206{col 72}{space 3} .9414875
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       399
{txt}{hline 13}{c +}{hline 34}   F(4, 394)       = {res}     0.69
{txt}       Model {c |} {res} .196032421         4  .049008105   {txt}Prob > F        ={res}    0.6004
{txt}    Residual {c |} {res} 28.0520814       394  .071198176   {txt}R-squared       ={res}    0.0069
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0031
{txt}       Total {c |} {res} 28.2481138       398   .07097516   {txt}Root MSE        =   {res} .26683

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_preexisting{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0396429{col 31}{space 2} .0412656{col 42}{space 1}   -0.96{col 51}{space 3}0.337{col 59}{space 4}-.1207712{col 72}{space 3} .0414854
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0040767{col 31}{space 2} .1324228{col 42}{space 1}    0.03{col 51}{space 3}0.975{col 59}{space 4}-.2562669{col 72}{space 3} .2644203
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0351898{col 31}{space 2} .0428597{col 42}{space 1}    0.82{col 51}{space 3}0.412{col 59}{space 4}-.0490725{col 72}{space 3} .1194522
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0611691{col 31}{space 2} .0575302{col 42}{space 1}    1.06{col 51}{space 3}0.288{col 59}{space 4}-.0519354{col 72}{space 3} .1742737
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7447887{col 31}{space 2}  .128721{col 42}{space 1}    5.79{col 51}{space 3}0.000{col 59}{space 4} .4917228{col 72}{space 3} .9978546
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       400
{txt}{hline 13}{c +}{hline 34}   F(4, 395)       = {res}     0.59
{txt}       Model {c |} {res} .204135447         4  .051033862   {txt}Prob > F        ={res}    0.6728
{txt}    Residual {c |} {res} 34.3896577       395  .087062425   {txt}R-squared       ={res}    0.0059
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0042
{txt}       Total {c |} {res} 34.5937932       399  .086701236   {txt}Root MSE        =   {res} .29506

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_jobs{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0357953{col 31}{space 2} .0454922{col 42}{space 1}   -0.79{col 51}{space 3}0.432{col 59}{space 4}-.1252324{col 72}{space 3} .0536418
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}  -.15384{col 31}{space 2} .1461748{col 42}{space 1}   -1.05{col 51}{space 3}0.293{col 59}{space 4}-.4412178{col 72}{space 3} .1335378
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} -.030235{col 31}{space 2} .0473005{col 42}{space 1}   -0.64{col 51}{space 3}0.523{col 59}{space 4}-.1232273{col 72}{space 3} .0627573
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .0214798{col 31}{space 2} .0634617{col 42}{space 1}    0.34{col 51}{space 3}0.735{col 59}{space 4} -.103285{col 72}{space 3} .1462447
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8302587{col 31}{space 2}  .141955{col 42}{space 1}    5.85{col 51}{space 3}0.000{col 59}{space 4} .5511769{col 72}{space 3} 1.109341
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       398
{txt}{hline 13}{c +}{hline 34}   F(4, 393)       = {res}     1.27
{txt}       Model {c |} {res} .474133877         4  .118533469   {txt}Prob > F        ={res}    0.2809
{txt}    Residual {c |} {res} 36.6621262       393  .093287853   {txt}R-squared       ={res}    0.0128
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0027
{txt}       Total {c |} {res} 37.1362601       397  .093542217   {txt}Root MSE        =   {res} .30543

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} covid_healthcare{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0738527{col 31}{space 2} .0472908{col 42}{space 1}   -1.56{col 51}{space 3}0.119{col 59}{space 4}-.1668272{col 72}{space 3} .0191218
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} -.186725{col 31}{space 2} .1516876{col 42}{space 1}   -1.23{col 51}{space 3}0.219{col 59}{space 4}-.4849457{col 72}{space 3} .1114958
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0050121{col 31}{space 2} .0490769{col 42}{space 1}    0.10{col 51}{space 3}0.919{col 59}{space 4} -.091474{col 72}{space 3} .1014981
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0733142{col 31}{space 2} .0659212{col 42}{space 1}   -1.11{col 51}{space 3}0.267{col 59}{space 4}-.2029165{col 72}{space 3} .0562882
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8785729{col 31}{space 2} .1474869{col 42}{space 1}    5.96{col 51}{space 3}0.000{col 59}{space 4} .5886109{col 72}{space 3} 1.168535
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       400
{txt}{hline 13}{c +}{hline 34}   F(4, 395)       = {res}     0.63
{txt}       Model {c |} {res} .192164455         4  .048041114   {txt}Prob > F        ={res}    0.6404
{txt}    Residual {c |} {res} 30.0566097       395  .076092683   {txt}R-squared       ={res}    0.0064
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0037
{txt}       Total {c |} {res} 30.2487742       399  .075811464   {txt}Root MSE        =   {res} .27585

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_neighborh~d{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0590677{col 31}{space 2} .0425298{col 42}{space 1}   -1.39{col 51}{space 3}0.166{col 59}{space 4}-.1426807{col 72}{space 3} .0245452
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0508728{col 31}{space 2} .1366559{col 42}{space 1}   -0.37{col 51}{space 3}0.710{col 59}{space 4}-.3195367{col 72}{space 3} .2177911
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0032089{col 31}{space 2} .0442204{col 42}{space 1}   -0.07{col 51}{space 3}0.942{col 59}{space 4}-.0901456{col 72}{space 3} .0837278
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0432068{col 31}{space 2} .0593291{col 42}{space 1}   -0.73{col 51}{space 3}0.467{col 59}{space 4} -.159847{col 72}{space 3} .0734335
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8112967{col 31}{space 2}  .132711{col 42}{space 1}    6.11{col 51}{space 3}0.000{col 59}{space 4} .5503885{col 72}{space 3} 1.072205
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:black} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:hispanic} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:api} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}       400
{txt}{hline 13}{c +}{hline 34}   F(4, 395)       = {res}     1.75
{txt}       Model {c |} {res} .572786192         4  .143196548   {txt}Prob > F        ={res}    0.1384
{txt}    Residual {c |} {res} 32.3348227       395  .081860311   {txt}R-squared       ={res}    0.0174
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0075
{txt}       Total {c |} {res} 32.9076088       399   .08247521   {txt}Root MSE        =   {res} .28611

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}covid_flout_pro~s{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2}-.0371037{col 31}{space 2} .0441121{col 42}{space 1}   -0.84{col 51}{space 3}0.401{col 59}{space 4}-.1238276{col 72}{space 3} .0496203
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1245555{col 31}{space 2} .1417404{col 42}{space 1}   -0.88{col 51}{space 3}0.380{col 59}{space 4}-.4032154{col 72}{space 3} .1541045
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} -.023228{col 31}{space 2} .0458656{col 42}{space 1}   -0.51{col 51}{space 3}0.613{col 59}{space 4}-.1133993{col 72}{space 3} .0669433
{txt}{space 12}age01 {c |}{col 19}{res}{space 2} .1369735{col 31}{space 2} .0615365{col 42}{space 1}    2.23{col 51}{space 3}0.027{col 59}{space 4} .0159935{col 72}{space 3} .2579535
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .8197742{col 31}{space 2} .1376487{col 42}{space 1}    5.96{col 51}{space 3}0.000{col 59}{space 4} .5491585{col 72}{space 3}  1.09039
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. suest covid_gene1 covid_gene2
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene1:covid_gene1}, {stata estimates replay covid_gene2:covid_gene2}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:751}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0324745{col 31}{space 2} .0588925{col 42}{space 1}    0.55{col 51}{space 3}0.581{col 59}{space 4}-.0829528{col 72}{space 3} .1479018
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0591964{col 31}{space 2} .0519622{col 42}{space 1}    1.14{col 51}{space 3}0.255{col 59}{space 4}-.0426477{col 72}{space 3} .1610405
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0742419{col 31}{space 2} .0603236{col 42}{space 1}    1.23{col 51}{space 3}0.218{col 59}{space 4}-.0439903{col 72}{space 3} .1924741
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.1568964{col 31}{space 2} .0785664{col 42}{space 1}   -2.00{col 51}{space 3}0.046{col 59}{space 4}-.3108838{col 72}{space 3}-.0029091
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .5631289{col 31}{space 2} .0647317{col 42}{space 1}    8.70{col 51}{space 3}0.000{col 59}{space 4}  .436257{col 72}{space 3} .6900008
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.304457{col 31}{space 2} .0588589{col 42}{space 1}  -39.15{col 51}{space 3}0.000{col 59}{space 4}-2.419818{col 72}{space 3}-2.189095
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .1058281{col 31}{space 2} .0504032{col 42}{space 1}    2.10{col 51}{space 3}0.036{col 59}{space 4} .0070397{col 72}{space 3} .2046165
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.3057266{col 31}{space 2} .0647003{col 42}{space 1}   -4.73{col 51}{space 3}0.000{col 59}{space 4}-.4325369{col 72}{space 3}-.1789163
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0999222{col 31}{space 2} .0624064{col 42}{space 1}   -1.60{col 51}{space 3}0.109{col 59}{space 4}-.2222365{col 72}{space 3} .0223921
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0823343{col 31}{space 2} .0742211{col 42}{space 1}   -1.11{col 51}{space 3}0.267{col 59}{space 4} -.227805{col 72}{space 3} .0631364
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7988455{col 31}{space 2}  .051267{col 42}{space 1}   15.58{col 51}{space 3}0.000{col 59}{space 4} .6983641{col 72}{space 3} .8993269
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.240517{col 31}{space 2} .0690139{col 42}{space 1}  -32.46{col 51}{space 3}0.000{col 59}{space 4}-2.375781{col 72}{space 3}-2.105252
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene1_mean]race_bio_identity = [covid_gene2_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene1_mean]race_bio_identity - [covid_gene2_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.90
{txt}{col 10}Prob > chi2 =  {res}  0.3440
{txt}
{com}. suest covid_gene1 covid_gene3
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene1:covid_gene1}, {stata estimates replay covid_gene3:covid_gene3}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:731}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0324745{col 31}{space 2} .0588936{col 42}{space 1}    0.55{col 51}{space 3}0.581{col 59}{space 4}-.0829549{col 72}{space 3} .1479039
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0591964{col 31}{space 2} .0519632{col 42}{space 1}    1.14{col 51}{space 3}0.255{col 59}{space 4}-.0426496{col 72}{space 3} .1610423
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0742419{col 31}{space 2} .0603247{col 42}{space 1}    1.23{col 51}{space 3}0.218{col 59}{space 4}-.0439924{col 72}{space 3} .1924762
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.1568964{col 31}{space 2} .0785678{col 42}{space 1}   -2.00{col 51}{space 3}0.046{col 59}{space 4}-.3108866{col 72}{space 3}-.0029063
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .5631289{col 31}{space 2} .0647329{col 42}{space 1}    8.70{col 51}{space 3}0.000{col 59}{space 4} .4362547{col 72}{space 3} .6900031
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.304457{col 31}{space 2}   .05886{col 42}{space 1}  -39.15{col 51}{space 3}0.000{col 59}{space 4} -2.41982{col 72}{space 3}-2.189093
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0533694{col 31}{space 2} .0545696{col 42}{space 1}    0.98{col 51}{space 3}0.328{col 59}{space 4}-.0535851{col 72}{space 3}  .160324
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1659894{col 31}{space 2} .0517784{col 42}{space 1}   -3.21{col 51}{space 3}0.001{col 59}{space 4}-.2674732{col 72}{space 3}-.0645056
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1071097{col 31}{space 2} .0601568{col 42}{space 1}   -1.78{col 51}{space 3}0.075{col 59}{space 4}-.2250147{col 72}{space 3} .0107954
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0473796{col 31}{space 2} .0795404{col 42}{space 1}   -0.60{col 51}{space 3}0.551{col 59}{space 4}-.2032758{col 72}{space 3} .1085167
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7841609{col 31}{space 2} .0533217{col 42}{space 1}   14.71{col 51}{space 3}0.000{col 59}{space 4} .6796522{col 72}{space 3} .8886696
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.288856{col 31}{space 2} .0695194{col 42}{space 1}  -32.92{col 51}{space 3}0.000{col 59}{space 4}-2.425112{col 72}{space 3}  -2.1526
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene1_mean]race_bio_identity = [covid_gene3_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene1_mean]race_bio_identity - [covid_gene3_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.07
{txt}{col 10}Prob > chi2 =  {res}  0.7947
{txt}
{com}. suest covid_gene1 covid_gene4
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene1:covid_gene1}, {stata estimates replay covid_gene4:covid_gene4}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:778}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0324745{col 31}{space 2} .0588912{col 42}{space 1}    0.55{col 51}{space 3}0.581{col 59}{space 4}-.0829501{col 72}{space 3} .1478991
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0591964{col 31}{space 2}  .051961{col 42}{space 1}    1.14{col 51}{space 3}0.255{col 59}{space 4}-.0426454{col 72}{space 3} .1610381
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0742419{col 31}{space 2} .0603222{col 42}{space 1}    1.23{col 51}{space 3}0.218{col 59}{space 4}-.0439875{col 72}{space 3} .1924713
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.1568964{col 31}{space 2} .0785646{col 42}{space 1}   -2.00{col 51}{space 3}0.046{col 59}{space 4}-.3108802{col 72}{space 3}-.0029126
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .5631289{col 31}{space 2} .0647302{col 42}{space 1}    8.70{col 51}{space 3}0.000{col 59}{space 4} .4362599{col 72}{space 3} .6899978
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.304457{col 31}{space 2} .0588575{col 42}{space 1}  -39.15{col 51}{space 3}0.000{col 59}{space 4}-2.419815{col 72}{space 3}-2.189098
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .2133851{col 31}{space 2} .0559133{col 42}{space 1}    3.82{col 51}{space 3}0.000{col 59}{space 4} .1037971{col 72}{space 3} .3229731
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0846483{col 31}{space 2} .1566252{col 42}{space 1}    0.54{col 51}{space 3}0.589{col 59}{space 4}-.2223315{col 72}{space 3} .3916281
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1760361{col 31}{space 2} .0463263{col 42}{space 1}   -3.80{col 51}{space 3}0.000{col 59}{space 4}-.2668339{col 72}{space 3}-.0852383
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .002533{col 31}{space 2} .0667182{col 42}{space 1}    0.04{col 51}{space 3}0.970{col 59}{space 4}-.1282323{col 72}{space 3} .1332984
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6271268{col 31}{space 2} .0585173{col 42}{space 1}   10.72{col 51}{space 3}0.000{col 59}{space 4}  .512435{col 72}{space 3} .7418186
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.295959{col 31}{space 2} .0609061{col 42}{space 1}  -37.70{col 51}{space 3}0.000{col 59}{space 4}-2.415333{col 72}{space 3}-2.176585
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene1_mean]race_bio_identity = [covid_gene4_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene1_mean]race_bio_identity - [covid_gene4_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    4.96
{txt}{col 10}Prob > chi2 =  {res}  0.0259
{txt}
{com}. /*p=0.026*/
. suest covid_gene1 covid_gene5
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene1:covid_gene1}, {stata estimates replay covid_gene5:covid_gene5}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:770}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0324745{col 31}{space 2} .0588916{col 42}{space 1}    0.55{col 51}{space 3}0.581{col 59}{space 4}-.0829509{col 72}{space 3} .1478999
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0591964{col 31}{space 2} .0519614{col 42}{space 1}    1.14{col 51}{space 3}0.255{col 59}{space 4}-.0426461{col 72}{space 3} .1610388
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0742419{col 31}{space 2} .0603227{col 42}{space 1}    1.23{col 51}{space 3}0.218{col 59}{space 4}-.0439883{col 72}{space 3} .1924721
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.1568964{col 31}{space 2} .0785651{col 42}{space 1}   -2.00{col 51}{space 3}0.046{col 59}{space 4}-.3108812{col 72}{space 3}-.0029116
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .5631289{col 31}{space 2} .0647307{col 42}{space 1}    8.70{col 51}{space 3}0.000{col 59}{space 4} .4362591{col 72}{space 3} .6899987
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene1_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.304457{col 31}{space 2} .0588579{col 42}{space 1}  -39.15{col 51}{space 3}0.000{col 59}{space 4}-2.419816{col 72}{space 3}-2.189097
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0202144{col 31}{space 2}  .050721{col 42}{space 1}    0.40{col 51}{space 3}0.690{col 59}{space 4} -.079197{col 72}{space 3} .1196257
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0433427{col 31}{space 2} .1518907{col 42}{space 1}   -0.29{col 51}{space 3}0.775{col 59}{space 4} -.341043{col 72}{space 3} .2543577
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0463857{col 31}{space 2} .0471054{col 42}{space 1}    0.98{col 51}{space 3}0.325{col 59}{space 4}-.0459393{col 72}{space 3} .1387106
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0334925{col 31}{space 2} .0673052{col 42}{space 1}   -0.50{col 51}{space 3}0.619{col 59}{space 4}-.1654083{col 72}{space 3} .0984232
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6525041{col 31}{space 2} .1451583{col 42}{space 1}    4.50{col 51}{space 3}0.000{col 59}{space 4}  .367999{col 72}{space 3} .9370091
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.376849{col 31}{space 2} .0582718{col 42}{space 1}  -40.79{col 51}{space 3}0.000{col 59}{space 4} -2.49106{col 72}{space 3}-2.262638
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene1_mean]race_bio_identity = [covid_gene5_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene1_mean]race_bio_identity - [covid_gene5_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.02
{txt}{col 10}Prob > chi2 =  {res}  0.8747
{txt}
{com}. suest covid_gene2 covid_gene3
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene2:covid_gene2}, {stata estimates replay covid_gene3:covid_gene3}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:740}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .1058281{col 31}{space 2} .0504037{col 42}{space 1}    2.10{col 51}{space 3}0.036{col 59}{space 4} .0070387{col 72}{space 3} .2046175
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.3057266{col 31}{space 2}  .064701{col 42}{space 1}   -4.73{col 51}{space 3}0.000{col 59}{space 4}-.4325382{col 72}{space 3} -.178915
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0999222{col 31}{space 2}  .062407{col 42}{space 1}   -1.60{col 51}{space 3}0.109{col 59}{space 4}-.2222377{col 72}{space 3} .0223933
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0823343{col 31}{space 2} .0742218{col 42}{space 1}   -1.11{col 51}{space 3}0.267{col 59}{space 4}-.2278064{col 72}{space 3} .0631379
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7988455{col 31}{space 2} .0512675{col 42}{space 1}   15.58{col 51}{space 3}0.000{col 59}{space 4} .6983631{col 72}{space 3} .8993279
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.240517{col 31}{space 2} .0690146{col 42}{space 1}  -32.46{col 51}{space 3}0.000{col 59}{space 4}-2.375783{col 72}{space 3} -2.10525
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0533694{col 31}{space 2} .0545692{col 42}{space 1}    0.98{col 51}{space 3}0.328{col 59}{space 4}-.0535842{col 72}{space 3} .1603231
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1659894{col 31}{space 2}  .051778{col 42}{space 1}   -3.21{col 51}{space 3}0.001{col 59}{space 4}-.2674724{col 72}{space 3}-.0645064
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1071097{col 31}{space 2} .0601563{col 42}{space 1}   -1.78{col 51}{space 3}0.075{col 59}{space 4}-.2250137{col 72}{space 3} .0107944
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0473796{col 31}{space 2} .0795397{col 42}{space 1}   -0.60{col 51}{space 3}0.551{col 59}{space 4}-.2032745{col 72}{space 3} .1085154
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7841609{col 31}{space 2} .0533213{col 42}{space 1}   14.71{col 51}{space 3}0.000{col 59}{space 4} .6796531{col 72}{space 3} .8886687
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.288856{col 31}{space 2} .0695188{col 42}{space 1}  -32.92{col 51}{space 3}0.000{col 59}{space 4} -2.42511{col 72}{space 3}-2.152602
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene2_mean]race_bio_identity = [covid_gene3_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene2_mean]race_bio_identity - [covid_gene3_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.50
{txt}{col 10}Prob > chi2 =  {res}  0.4801
{txt}
{com}. suest covid_gene2 covid_gene4
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene2:covid_gene2}, {stata estimates replay covid_gene4:covid_gene4}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:787}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .1058281{col 31}{space 2} .0504016{col 42}{space 1}    2.10{col 51}{space 3}0.036{col 59}{space 4} .0070427{col 72}{space 3} .2046135
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.3057266{col 31}{space 2} .0646984{col 42}{space 1}   -4.73{col 51}{space 3}0.000{col 59}{space 4}-.4325331{col 72}{space 3}-.1789201
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0999222{col 31}{space 2} .0624045{col 42}{space 1}   -1.60{col 51}{space 3}0.109{col 59}{space 4}-.2222327{col 72}{space 3} .0223884
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0823343{col 31}{space 2} .0742188{col 42}{space 1}   -1.11{col 51}{space 3}0.267{col 59}{space 4}-.2278005{col 72}{space 3}  .063132
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7988455{col 31}{space 2} .0512654{col 42}{space 1}   15.58{col 51}{space 3}0.000{col 59}{space 4} .6983672{col 72}{space 3} .8993238
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.240517{col 31}{space 2} .0690118{col 42}{space 1}  -32.47{col 51}{space 3}0.000{col 59}{space 4}-2.375777{col 72}{space 3}-2.105256
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .2133851{col 31}{space 2} .0559129{col 42}{space 1}    3.82{col 51}{space 3}0.000{col 59}{space 4} .1037979{col 72}{space 3} .3229723
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0846483{col 31}{space 2} .1566241{col 42}{space 1}    0.54{col 51}{space 3}0.589{col 59}{space 4}-.2223293{col 72}{space 3} .3916258
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1760361{col 31}{space 2} .0463259{col 42}{space 1}   -3.80{col 51}{space 3}0.000{col 59}{space 4}-.2668332{col 72}{space 3} -.085239
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .002533{col 31}{space 2} .0667177{col 42}{space 1}    0.04{col 51}{space 3}0.970{col 59}{space 4}-.1282313{col 72}{space 3} .1332974
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6271268{col 31}{space 2} .0585169{col 42}{space 1}   10.72{col 51}{space 3}0.000{col 59}{space 4} .5124358{col 72}{space 3} .7418178
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.295959{col 31}{space 2} .0609056{col 42}{space 1}  -37.70{col 51}{space 3}0.000{col 59}{space 4}-2.415332{col 72}{space 3}-2.176586
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene2_mean]race_bio_identity = [covid_gene4_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene2_mean]race_bio_identity - [covid_gene4_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.04
{txt}{col 10}Prob > chi2 =  {res}  0.1531
{txt}
{com}. suest covid_gene2 covid_gene5
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene2:covid_gene2}, {stata estimates replay covid_gene5:covid_gene5}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:779}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .1058281{col 31}{space 2}  .050402{col 42}{space 1}    2.10{col 51}{space 3}0.036{col 59}{space 4} .0070421{col 72}{space 3} .2046141
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.3057266{col 31}{space 2} .0646988{col 42}{space 1}   -4.73{col 51}{space 3}0.000{col 59}{space 4}-.4325339{col 72}{space 3}-.1789193
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0999222{col 31}{space 2} .0624049{col 42}{space 1}   -1.60{col 51}{space 3}0.109{col 59}{space 4}-.2222335{col 72}{space 3} .0223892
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0823343{col 31}{space 2} .0742193{col 42}{space 1}   -1.11{col 51}{space 3}0.267{col 59}{space 4}-.2278015{col 72}{space 3} .0631329
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7988455{col 31}{space 2} .0512657{col 42}{space 1}   15.58{col 51}{space 3}0.000{col 59}{space 4} .6983665{col 72}{space 3} .8993245
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene2_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.240517{col 31}{space 2} .0690123{col 42}{space 1}  -32.47{col 51}{space 3}0.000{col 59}{space 4}-2.375778{col 72}{space 3}-2.105255
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0202144{col 31}{space 2} .0507206{col 42}{space 1}    0.40{col 51}{space 3}0.690{col 59}{space 4}-.0791962{col 72}{space 3} .1196249
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0433427{col 31}{space 2} .1518896{col 42}{space 1}   -0.29{col 51}{space 3}0.775{col 59}{space 4}-.3410408{col 72}{space 3} .2543554
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0463857{col 31}{space 2} .0471051{col 42}{space 1}    0.98{col 51}{space 3}0.325{col 59}{space 4}-.0459386{col 72}{space 3} .1387099
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0334925{col 31}{space 2} .0673047{col 42}{space 1}   -0.50{col 51}{space 3}0.619{col 59}{space 4}-.1654073{col 72}{space 3} .0984222
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6525041{col 31}{space 2} .1451572{col 42}{space 1}    4.50{col 51}{space 3}0.000{col 59}{space 4} .3680011{col 72}{space 3}  .937007
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.376849{col 31}{space 2} .0582714{col 42}{space 1}  -40.79{col 51}{space 3}0.000{col 59}{space 4}-2.491059{col 72}{space 3}-2.262639
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene2_mean]race_bio_identity = [covid_gene5_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene2_mean]race_bio_identity - [covid_gene5_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.43
{txt}{col 10}Prob > chi2 =  {res}  0.2312
{txt}
{com}. suest covid_gene3 covid_gene4
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene3:covid_gene3}, {stata estimates replay covid_gene4:covid_gene4}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:767}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0533694{col 31}{space 2} .0545679{col 42}{space 1}    0.98{col 51}{space 3}0.328{col 59}{space 4}-.0535816{col 72}{space 3} .1603205
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1659894{col 31}{space 2} .0517768{col 42}{space 1}   -3.21{col 51}{space 3}0.001{col 59}{space 4}  -.26747{col 72}{space 3}-.0645088
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1071097{col 31}{space 2} .0601548{col 42}{space 1}   -1.78{col 51}{space 3}0.075{col 59}{space 4}-.2250109{col 72}{space 3} .0107916
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0473796{col 31}{space 2} .0795378{col 42}{space 1}   -0.60{col 51}{space 3}0.551{col 59}{space 4}-.2032708{col 72}{space 3} .1085117
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7841609{col 31}{space 2}   .05332{col 42}{space 1}   14.71{col 51}{space 3}0.000{col 59}{space 4} .6796556{col 72}{space 3} .8886662
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.288856{col 31}{space 2} .0695172{col 42}{space 1}  -32.93{col 51}{space 3}0.000{col 59}{space 4}-2.425107{col 72}{space 3}-2.152605
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .2133851{col 31}{space 2} .0559138{col 42}{space 1}    3.82{col 51}{space 3}0.000{col 59}{space 4}  .103796{col 72}{space 3} .3229741
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0846483{col 31}{space 2} .1566267{col 42}{space 1}    0.54{col 51}{space 3}0.589{col 59}{space 4}-.2223343{col 72}{space 3} .3916309
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1760361{col 31}{space 2} .0463267{col 42}{space 1}   -3.80{col 51}{space 3}0.000{col 59}{space 4}-.2668347{col 72}{space 3}-.0852375
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .002533{col 31}{space 2} .0667188{col 42}{space 1}    0.04{col 51}{space 3}0.970{col 59}{space 4}-.1282335{col 72}{space 3} .1332996
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6271268{col 31}{space 2} .0585178{col 42}{space 1}   10.72{col 51}{space 3}0.000{col 59}{space 4} .5124339{col 72}{space 3} .7418197
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.295959{col 31}{space 2} .0609066{col 42}{space 1}  -37.70{col 51}{space 3}0.000{col 59}{space 4}-2.415334{col 72}{space 3}-2.176584
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene3_mean]race_bio_identity = [covid_gene4_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene3_mean]race_bio_identity - [covid_gene4_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    4.19
{txt}{col 10}Prob > chi2 =  {res}  0.0405
{txt}
{com}. /*p=0.0405*/
. suest covid_gene3 covid_gene5
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene3:covid_gene3}, {stata estimates replay covid_gene5:covid_gene5}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:759}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0533694{col 31}{space 2} .0545683{col 42}{space 1}    0.98{col 51}{space 3}0.328{col 59}{space 4}-.0535824{col 72}{space 3} .1603212
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1659894{col 31}{space 2} .0517771{col 42}{space 1}   -3.21{col 51}{space 3}0.001{col 59}{space 4}-.2674707{col 72}{space 3}-.0645081
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1071097{col 31}{space 2} .0601552{col 42}{space 1}   -1.78{col 51}{space 3}0.075{col 59}{space 4}-.2250118{col 72}{space 3} .0107924
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0473796{col 31}{space 2} .0795384{col 42}{space 1}   -0.60{col 51}{space 3}0.551{col 59}{space 4}-.2032719{col 72}{space 3} .1085127
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .7841609{col 31}{space 2} .0533204{col 42}{space 1}   14.71{col 51}{space 3}0.000{col 59}{space 4} .6796549{col 72}{space 3}  .888667
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene3_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.288856{col 31}{space 2} .0695176{col 42}{space 1}  -32.92{col 51}{space 3}0.000{col 59}{space 4}-2.425108{col 72}{space 3}-2.152604
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0202144{col 31}{space 2} .0507215{col 42}{space 1}    0.40{col 51}{space 3}0.690{col 59}{space 4}-.0791979{col 72}{space 3} .1196266
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0433427{col 31}{space 2} .1518922{col 42}{space 1}   -0.29{col 51}{space 3}0.775{col 59}{space 4}-.3410458{col 72}{space 3} .2543605
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0463857{col 31}{space 2} .0471059{col 42}{space 1}    0.98{col 51}{space 3}0.325{col 59}{space 4}-.0459402{col 72}{space 3} .1387115
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0334925{col 31}{space 2} .0673058{col 42}{space 1}   -0.50{col 51}{space 3}0.619{col 59}{space 4}-.1654095{col 72}{space 3} .0984244
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6525041{col 31}{space 2} .1451597{col 42}{space 1}    4.50{col 51}{space 3}0.000{col 59}{space 4} .3679963{col 72}{space 3} .9370118
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.376849{col 31}{space 2} .0582724{col 42}{space 1}  -40.79{col 51}{space 3}0.000{col 59}{space 4}-2.491061{col 72}{space 3}-2.262637
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene3_mean]race_bio_identity = [covid_gene5_mean]race_bio_identity

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene3_mean]race_bio_identity - [covid_gene5_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.20
{txt}{col 10}Prob > chi2 =  {res}  0.6563
{txt}
{com}. suest covid_gene4 covid_gene5
{res}
{txt}Simultaneous results for {stata estimates replay covid_gene4:covid_gene4}, {stata estimates replay covid_gene5:covid_gene5}

{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:806}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .2133851{col 31}{space 2}  .055912{col 42}{space 1}    3.82{col 51}{space 3}0.000{col 59}{space 4} .1037995{col 72}{space 3} .3229707
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2} .0846483{col 31}{space 2} .1566217{col 42}{space 1}    0.54{col 51}{space 3}0.589{col 59}{space 4}-.2223247{col 72}{space 3} .3916212
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.1760361{col 31}{space 2} .0463252{col 42}{space 1}   -3.80{col 51}{space 3}0.000{col 59}{space 4}-.2668319{col 72}{space 3}-.0852403
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}  .002533{col 31}{space 2} .0667167{col 42}{space 1}    0.04{col 51}{space 3}0.970{col 59}{space 4}-.1282294{col 72}{space 3} .1332954
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6271268{col 31}{space 2}  .058516{col 42}{space 1}   10.72{col 51}{space 3}0.000{col 59}{space 4} .5124376{col 72}{space 3}  .741816
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene4_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.295959{col 31}{space 2} .0609047{col 42}{space 1}  -37.70{col 51}{space 3}0.000{col 59}{space 4} -2.41533{col 72}{space 3}-2.176588
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_mean  {txt}{c |}
race_bio_identity {c |}{col 19}{res}{space 2} .0202144{col 31}{space 2} .0507195{col 42}{space 1}    0.40{col 51}{space 3}0.690{col 59}{space 4}-.0791941{col 72}{space 3} .1196228
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.0433427{col 31}{space 2} .1518863{col 42}{space 1}   -0.29{col 51}{space 3}0.775{col 59}{space 4}-.3410344{col 72}{space 3}  .254349
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2} .0463857{col 31}{space 2} .0471041{col 42}{space 1}    0.98{col 51}{space 3}0.325{col 59}{space 4}-.0459366{col 72}{space 3} .1387079
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0334925{col 31}{space 2} .0673032{col 42}{space 1}   -0.50{col 51}{space 3}0.619{col 59}{space 4}-.1654044{col 72}{space 3} .0984194
{txt}{space 12}black {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 9}hispanic {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 14}api {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 12}_cons {c |}{col 19}{res}{space 2} .6525041{col 31}{space 2} .1451541{col 42}{space 1}    4.50{col 51}{space 3}0.000{col 59}{space 4} .3680073{col 72}{space 3} .9370009
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}covid_gene5_lnvar {txt}{c |}
{space 12}_cons {c |}{col 19}{res}{space 2}-2.376849{col 31}{space 2} .0582701{col 42}{space 1}  -40.79{col 51}{space 3}0.000{col 59}{space 4}-2.491056{col 72}{space 3}-2.262642
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test [covid_gene4_mean]race_bio_identity = [covid_gene5_mean]race_bio_identity 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[covid_gene4_mean]race_bio_identity - [covid_gene5_mean]race_bio_identity = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    6.55
{txt}{col 10}Prob > chi2 =  {res}  0.0105
{txt}
{com}. /*p=0.0105*/
. 
. //analyzing the four other groups together, without WDem//
. reg covid_gene race_bio_identity pid7cata ed6cat age01 black hispanic api if fivegroups~=4 & ref_covid_battery~=6

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,524
{txt}{hline 13}{c +}{hline 34}   F(7, 1516)      = {res}     8.84
{txt}       Model {c |} {res} 6.25250139         7  .893214484   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 153.199941     1,516   .10105537   {txt}R-squared       ={res}    0.0392
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0348
{txt}       Total {c |} {res} 159.452442     1,523  .104696285   {txt}Root MSE        =   {res} .31789

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       covid_gene{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
race_bio_identity {c |}{col 19}{res}{space 2} .0642775{col 31}{space 2} .0255792{col 42}{space 1}    2.51{col 51}{space 3}0.012{col 59}{space 4} .0141033{col 72}{space 3} .1144518
{txt}{space 9}pid7cata {c |}{col 19}{res}{space 2}-.1286343{col 31}{space 2} .0300906{col 42}{space 1}   -4.27{col 51}{space 3}0.000{col 59}{space 4} -.187658{col 72}{space 3}-.0696107
{txt}{space 11}ed6cat {c |}{col 19}{res}{space 2}-.0300365{col 31}{space 2} .0276248{col 42}{space 1}   -1.09{col 51}{space 3}0.277{col 59}{space 4}-.0842234{col 72}{space 3} .0241504
{txt}{space 12}age01 {c |}{col 19}{res}{space 2}-.0699894{col 31}{space 2} .0364037{col 42}{space 1}   -1.92{col 51}{space 3}0.055{col 59}{space 4}-.1413963{col 72}{space 3} .0014175
{txt}{space 12}black {c |}{col 19}{res}{space 2}-.0082752{col 31}{space 2} .0310293{col 42}{space 1}   -0.27{col 51}{space 3}0.790{col 59}{space 4}  -.06914{col 72}{space 3} .0525897
{txt}{space 9}hispanic {c |}{col 19}{res}{space 2}-.0182544{col 31}{space 2} .0290388{col 42}{space 1}   -0.63{col 51}{space 3}0.530{col 59}{space 4}-.0752149{col 72}{space 3}  .038706
{txt}{space 14}api {c |}{col 19}{res}{space 2}-.0983064{col 31}{space 2} .0284479{col 42}{space 1}   -3.46{col 51}{space 3}0.001{col 59}{space 4}-.1541078{col 72}{space 3}-.0425049
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7565476{col 31}{space 2} .0410345{col 42}{space 1}   18.44{col 51}{space 3}0.000{col 59}{space 4} .6760572{col 72}{space 3}  .837038
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\users\kamcd\Dropbox\CDK WORK\racial disparities essentialism\JOP replication files\Anoll Kam Marcellin Lucid Analyses.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}10 Jan 2025, 14:29:19
{txt}{.-}
{smcl}
{txt}{sf}{ul off}